#cui yi xin

[xiaolanhua]

The Love You Give Me 你给我的喜欢 (2023) Dir. by. Ding Ying Zhou

[lostinadrama]

𝐓𝐡𝐞 𝐋𝐨𝐯𝐞 𝐘𝐨𝐮 𝐆𝐢𝐯𝐞 𝐌𝐞 (2023)

[nemainofthewater]

Welcome to the 'Best Character with [X] surname' polls!

This is where I take several characters from different Chinese media (mostly cnovels and cdrama) and run a poll on which one is the 'best'. What does best mean? It's up to you! Whether you love them, are intrigued by their characters, love to hate them, or they're your '2 second blorbos whose personality you made up wholesale', these are all reasons for you to vote for your favs!

NB: the surnames are not exactly the same in all the cases, as often they will be a different character. I am, however, grouping them all together otherwise things got more complicated.

If you can't find a surname, it's because I couldn't find enough candidates (at least 3 from 3 distinct medias) to compete. Feel free to submit candidates!

I will be posting several polls at a time, so do come back and check this masterpost to remember which polls are ongoing, who the winners are, and who's coming up next!

Finished polls: Xing/Rong/Nan/Ren/Pan/Qu/Fu/Sui/Tan/You/Sima/Xuan/Chang/Xun/Shangguan/Jian/Qian/Shu/Xi/Yuwen/Cai/Sha/Yin/Ceng/Helian/Zeng/Lou/Mi/Ji/Ping/Tong/Tuoba/Ge/Murong/Hei/Niu/Tao/Si/Pang/Zi/Gongsun/Mao/Qing/Lian

Chi/Shan/Tian/Dao/Chao/Xin/Ran/Sang/Cang/Miao/Yao/Zang/Chong/Nangong/Kong/Hai/Deng/Kang/Jun/Chun/Gui/Peng/Gong/Dai/Bao/Bian/Leng/Xian/Kan/Hou/Shao/Kou/Zuo/Lai/Tie/Huan/Min/Xiong/Cen/Dou/Misc

There's only a certain number of hyperlinks that can be added per post, so the rest of the completed polls can now be found here

All the details of the individual polls under the readmore

An - posted 15/03/24 WINNER An Zhe

Bai - posted 28/02/24 WINNER Bai Fengxi

Baili - posted 22/03/24 WINNER Baili Qingmiao

Bao - posted 1/05/24 WINNER Bao Rongxing

Bi - posted 26/03/24 WINNER Bi Changfeng

Bian - posted 1/05/14 WINNER Bian Cheng

Cai - posted 7/04/24 WINNER Cai Quan

Cang - posted 23/04/24 WINNER Cang Jiumin

Cao - posted 8/02/24. WINNER - Cao Weining

Cen - posted 7/05/24 WINNEER Cen Xiao

Ceng - posted 8/04/24 WINNER Ceng Aiyu

Chang - posted 3/04/24 WINNER Chang Geng

Chao - posted 21/04/24 WINNER Chao Zi

Chen - posted 9/02/24 WINNER Chen Qingxu

Cheng - posted 10/03/24 WINNER Cheng Shaoshang

Chi - posted 19/04/24 WINNERS Chi Zhanggui and Chi Xiaochi

Chong - posted 25/04/24 WINNER Chong Ming

Chu - posted 12/03/24 WINNER Chu Wanning

Chun - posted 28/04/24 WINNER Chun Shen

Cui - posted 11/03/24 WINNER Madam Cui

Dai - posted 30/04/24 WINNER Dai Mubai

Dao - posted 20/04/24 WINNER Dao Mingsi

Deng - posted 27/04/24 WINNER Deng Kuan

Di - posted 16/02/24 WINNER Di Feisheng

Ding - posted 7/03/24 WINNER Ding Rong

Dong - posted 21/03/24 WINNER Dong Yi

Dongfang - posted 25/03/24 WINNER Dongfang Qingcang

Dou - posted 7/05/24 WINNER Dou Cheng

Du - posted 26/03/24 WINNER Du Cheng

Duan - posted 23/03/24 WINNER Duan Baiyue

Fan - posted 27/02/24 WINNER Fan Xian

Fang - posted 24/02/24 WINNER Fang Duobing

Fei - posted 20/03/24 WINNER Fei Du

Feng - posted 28/02/24 WINNER 'Other'

Fu - posted 31/03/24 WINNER Fu Yao

Gao - posted 13/02/24 WINNER Gao Xiaolian

Ge - posted 13/04/24 WINNER Ge Chen

Gong - posted 30/04/24 WINNER Gong Yu

Gongsun - posted 17/04/24 WINNER Gongsun Heng

Gu - posted 7/03/24 WINNER Gu Xiang

Guan - posted 17/03/24 WINNER Guan Hemeng

Gui - posted 29/04/24 WINNERS Gui Wen, Gui Yang, Gui Bai and 'Other'

Guo - posted 9/02/24 WINNER Guo Changcheng

Hai - posted 26/04/24 WINNER Hai Lanshi

Han - posted 17/03/24 WINNER Han Ying

Hao - posted 16/03/24 WINNER Hao Du

He - posted 22/03/24 WINNER He Xuan

Hei - posted 14/04/24 WINNER Hei Xiazi

Helian - posted 9/04/24 wINNER Helian Yi

Hong - posted 8/03/24 WINNER Hong Qigong

Hou - posted 3/05/24 WINNER Hou Bin

Hu - posted 6/03/24 WINNER Hu Tianying

Hua - posted 21/02/24 WINNER Hua Cheng

Huan - posted 6/05/24 WINNER Huan Xiaoyan

Huang - posted 20/03/24 WINNER Huang Shaotian

Huo - posted 25/02/24 WINNER Huo Xiuxiu

Ji - posted 11/04/24 WINNER Ji Xue

Jia - posted 18/03/24 WINNER Jia Kui

Jian - posted 4/04/24 WINNER Jian Buzhi

Jiang - posted 12/02/24 WINNER Jiang Cheng

Jiao - posted 27/03/24 WINNER Jiao Liqiao

Jin - posted 29/02/24 WINNER Jin Ling

Jing - posted 14/03/24 WINNER Jing Beiyuan

Jun - posted 28/04/24 WINNER 'Other"

Kan - posted 3/05/24 WINNER Kan Jian

Kang - posted 27/04/24 WINNER 'Other'

Kong - posted 26/04/24 WINNERS Kong Xiu and Alexis Kong

Kou - posted 4/05/24 WINNER Kou Baimen

Lai - posted 5/05/24 WINNER Lai Zhongshu

Lan - posted 23/02/24 WINNER Lan Wangji

Lei - posted 12/03/24 WINNER Lei Wujie

Leng - posted 2/05/24 WINNER Leng Yue

Li - posted 18/02/24 WINNER Li Lianhua

Lian - posted 18/04/24 WINNERS Lian Yufan and Lian Qiao

Liang - posted 13/03/24 WINNER 'Other'

Lin - posted 14/02/24 WINNER Lin Chen

Ling - posted 6/03/24 WINNER Ling Wen

Liu - posted 16/02/24 WINNER Liu Qingge

Long - posted 23/03/24 WINNER Long Zhi

Lou - posted 10/04/24 WINNER Lou Yao

Lu - posted 5/03/24 WINNER Lu Guang

Luo - posted 24/02/24 WINNER Luo Binghe

Ma - posted 13/03/24 WINNER Ma Xiuying

Mao - posted 17/04/24 WINNER Mao Panfeng

Mei - posted 14/02/24 WINNER Mei Changsu

Meng - posted 29/02/24 WINNER Meng Zhi

Mi - posted 10/04/24 WINER Mi Chong

Miao - posted 23/04/24 WINNER Miao Renfeng

Min - posted 6/05/24 WINNER Min Yunzhong

Ming - posted 26/02/24 WINNER Ming Yi

Misc - posted 7/05/24 WINNER Gongyi Xiao

Mo - posted 18/02/24 WINNER Mo Xuanyu

Mu - posted 22/02/24 WINNER Mu Nihuang

Murong - posted 13/04/24 WINNER Other

Nan - posted 29/03/24 WINNER Nan Feng

Nangong - posted 25/04/24 WINNER Nangong Si

Nie - posted 15/03/24 WINNER Nie Huaisang

Ning - posted 19/03/24 WINNER Ning Yingying

Niu - posted 14/04/24 WINNER Niu Chunmiao

Ouyang - posted 5/03/24 WINNER Ouyang Zizhen

Pan - posted 30/03/24 WINNER Pan Zi

Pang - posted 16/04/24 WINNER Pang Yizhi

Pei - posted 20/02/24 WINNER Pei Ming

Peng - posted 29/04/24 wINNER Peng Sanbian

Ping - posted 11/04/24 WINNER Ping An

Qi - posted 22/02/24 WINNER 'Other'

Qian - posted 5/04/24 WINNER Qian Jin

Qiao - posted 10/02/24 WINNER Qiao Wanmian

Qin - posted 16/03/24 WINNER Qin Banruo

Qing - posted 18/04/24 WINNER Qing Ge

Qiu - posted 25/03/24 WINNER Qiu Congxue

Qu - posted 30/03/24 WINNER Qu Lingfeng

Ran - posted 22/04/24 WINNERS Ran Lin and Ran Yun

Ren - posted 29/03/24 WINNER Ren Ruyi

Rong - posted 28/03/24 WINNER Rong Changqing

Ruan - posted 21/03/24 WINNER Ruan Nanzhu

Sang - posted 22/04/24 WINNER Sang Zan

Sha - posted 7/04/24 WINNER Sha Hualing

Shan - posted 19/04/24 WINNER Shan Gudao

Shang - posted 3/03/24 WINNER Shang Qinghua

Shangguan - posted 4/04/24 WINNER Shangguan Qin

Shao - posted 4/05/24 WINNER Shao Lin

Shen - posted 23/02/24 WINNER Shen Wei

Sheng - posted 4/03/24 WINNER Sheng Minglan

Sima - posted 2/04/24 WINNER Sima Yi

Shi - posted 8/03/24 WINNER Shi Qingxuan

Shu - posted 5/04/24 WINNER Shu Yanyan

Si - posted 15/04/24 WINNER Si Yilin

Song - posted 19/02/24 WINNER Song Lan

Su - posted 13/02/24 WINNER Su Zhe

Sun - posted 15/02/24 WINNER Sun Wukong

Sui - posted 31/03/24 WINNER Sui Zhou

Tan - posted 1/04/24 WINNER 'Other'

Tang - posted 12/02/24 WINNER Tang Fan

Tao - posted 15/04/24 WINNER Tao Ran

Tian - posted 20/04/24 WINNER Tian Qi

Tie - posted 5/05/24 WINNERS Tie Yinyi and Tie Miansheng

Tong - posted 12/04/24 WINNER Tong Lu

Tuoba - posted 12/04/24 WINNER Tuoba Yan

Wan - posted 24/03/24 WINNER Consort Wan

Wang - posted 26/02/24 WINNER Wang Pangzi

Wei - posted 8/02/24 WINNER Wei Wuxian

Wen - posted 2/03/24 WINNER Wen Kexing

Wu - posted 15/02/24 WINNER Wu Xie

Xi - posted 6/04/24 WINNER Xi Ping

Xia - posted 11/03/24 WINNER Xia Dong

Xian - posted 2/05/24 WINNERS Xian Ge and Xian Qing

Xiang - posted 19/03/24 WINNER Xiang Liu and Xiang Nanfang

Xiao - posted 20/02/24 WINNER Xiao Jingyan

Xie - posted 21/02/24 WINNER Xie Lian

Xin - posted 21/04/24 WINNER Xin Ziyuan

Xing - posted 28/03/24 WINNER Xing Zhi

Xiong - posted 7/05/24 WINNERS Xiong yipei and Xiong Chumo

Xu - posted 25/02/24 WINNER Xu Da

Xun - posted 3/04/24 WINNER Xun Feizhan

Xuan - posted 2/04/24 WINNER Xuan Shen'an | The Empress

Xue -posted 11/02/24 WINNER Xue Yang

Yan - posted 19/02/24 WINNER Yan Wushi

Yang - posted 3/03/24 WINNER Yang Wuxie

Yao - posted 24/04/24 WINNER Yao Zhen

Ye - posted 10/02/24 WINNER Ye Baiyi

Yi - posted 9/03/24 WINNER Yi Bichen

Yin - posted 8/04/24 WINNER Yin Yu

Ying - posted 17/02/24 WINNER Ying Hecong

You - posted 1/04/24 WINNER You Huo

Yu - posted 11/02/23 WINNER Yu Ziyuan

Yun - posted 1/03/24 WINNER Yun Biqiu

Yuan - posted 27/02/24 WINNER Yuan Boya

Yue - posted 4/03/24 WINNER Yue Qingyuan

Yuwen - posted 6/04/24 WINNER Yuwen Xuan

Zang - posted 24/02/24 WINNER Zang Ming

Zeng - posted 9/04/24 WINNER Zeng Xiangdong

Zhan - posted 10/03/24 WINNER Zhan Yunfei

Zhang - posted 17/02/24 WINNER Zhang Qiling

Zhao - posted 1/03/24 WINNER Zhao Yunlan

Zhen - posted 24/03/24 WINNER Zhen Ping

Zhi - posted 14/03/24 WINNER Zhi Xiu

Zhong - posted 27/03/24 WINNER Zhong Li

Zhou - posted 2/02/24 WINNER Zhou Zishu

Zhu - posted 9/03/24 Winner Zhu Hong

Zhuge - posted 18/03/24 WINNER Zhuge Liang

Zi - posted 16/04/24 WINNER 'Other'

Zuo - posted 5/05/24 WINNER Zuo Ran

[hunxi-after-hours]

introducing the candidates for danmei awards 2.0 (2022)

I’m hard at work on (procrastinating on the writing of) this year’s danmei awards, so I figured I’d introduce all of the candidates since I’ve gone pretty far off the map at this point and don’t expect anyone to recognize most of these titles asdlfkads (别问，问就知北极圈的冷)

a table of contents!

《小蘑菇》 Xiao Mo Gu by 一十四洲 Yi Shi Si Zhou

《不小心救了江湖公敌》 Bu Xiao Xin Jiu Le Jianghu Gong Di by 六木乔 Liu Muqiao (有声漫画 audiomanhua season 1)

《无双》 Wu Shuang by 梦溪石 Meng Xishi

《问鹿三千》 Wen Lu San Qian by 光合积木 Voicegem, 吼浪文化 Houlang Studio, and 斗木獬编剧工作室 Doumuxie Screenwriting Studio

《师弟还不杀我灭口》 Shidi Hai Bu Sha Wo Mie Kou by 子鹿 Zi Lu

《默读》 Mo Du by priest

《督主有病》 Du Zhu You Bing by 杨溯 Yang Su

《海中爵》 Hai Zhong Jue by 七药 Qi Yao

《哏儿》 Gen’er by 南北逐风 Nan Bei Zhu Feng

《杀破狼》 Sha Po Lang by priest

《金牌助理之弯弯没想到》 Jin Pai Zhu Li zhi Wan Wan Mei Xiang Dao by (nominally) 非天夜翔 Fei Tian Ye Xiang and (mostly) 传奇火箭队 The Legendary Rocket Team

#1: 《小蘑菇》 by 一十四洲 (full length crash course here)

genre(s): apocalyptic science fiction

mediums: original novel on JJWXC, audiodrama by 729声工厂 / 729 Voice Studio on 猫耳FM

in a world where genetic mutations threaten to destroy humankind and a man-made aurora dances across the sky each night, a sentient mushroom goes undercover in a human city to recover a part of himself that was stolen. a book that investigates humanity and personhood, sentience and benevolence, the role of order in a lawless world, how to face despair and the end times with dignity and meaning. also, mushroom-based comedy

#2: 《不小心救了江湖公敌》 Bu Xiao Xin Jiule Jianghu Gong Di by 六木乔 Liu Muqiao (有声漫画 audiomanhua season 1)

genre(s): wuxia

mediums: manhua on bilibili comics, audiomanhua by 回声漫响工作室 Huisheng Manxiang Studio on 猫耳FM. both ongoing

when Liu Jianghe, a feared demonic sect leader, turns up half-dead on Lu Qingyun’s doorstep, the reclusive jianghu doctor reluctantly saves Liu Jianghe’s life. but Liu Jianghe’s enemies are almost as numerous as his secrets, and soon, the two are dragged into the turmoil of jianghu intrigue and conspiracy. Lu Qingyun has his own hidden past, Liu Jianghe his own mysterious motivations, and neither of them are held back by something as silly as moral scruples. an audiomanhua about the vortex of jianghu politics, in which every single character is a villain

#3: 《无双》 Wu Shuang by 梦溪石 Meng Xishi

genre(s): wuxia, political intrigue

mediums: original novel on JJWXC

a few years after the end of 《千秋》 Qian Qiu, unrest returns to the newly-founded Sui Dynasty as domestic intrigue and foreign plots threaten to fracture the hard-won peace. Feng Xiao, an unbelievably handsome government official who moonlights as the sect leader of the demonic Fajing Zong, finds his unexpected match in the frail wandering Daoist Cui Buqu. But beneath Cui Buqu’s waning health are more secrets than Feng Xiao can guess at, and the fate of the Sui Dynasty rests on these two setting aside their rivalry long enough to work together. a book about roasting your rival first, saving your dynasty second, and maybe, just maybe, falling in love in the process

#4: 《问鹿三千》 Wen Lu San Qian by 光合积木 Voicegem, 吼浪文化 Houlang Studio, and 斗木獬编剧工作室 Doumuxie Screenwriting Studio (full length crash course here)

genre(s): wuxia, xuanhuan

mediums: audiodrama on 猫耳FM, ongoing

an intricate, interlocking serial narrative following four intertwining stories: a famous zither master investigating a new, mysterious rival, a cat yao impersonating a prince and the assassin sent to kill him, the obsessive quest of an emperor searching for a lost dao and the person who lived inside it, and two spirits seeking their forgotten pasts. oh, and a former king-turned-talking-rabbit. an audiodrama about fate and loyalty, devotion and trauma, memory and grief, love and loss

#5: 《师弟还不杀我灭口》 Shidi Hai Bu Sha Wo Mie Kou by 子鹿 Zi Lu

genre(s): xianxia, transmigration

mediums: original novel on 长佩 Changpei, audiodrama by 米波文化 Mibo Culture on 猫耳FM. AD trailer 1 translated here, AD trailer 2 translated here.

when college student Zhong Yan is drawn into the world of the xianxia novel he just finished instead of studying for his exams, his sympathy for the book’s antagonist lands him a near-impossible mission: stop the antagonist from killing more people, or risk the consequences of failure. now, if only he hadn’t transmigrated as the antagonist’s useless shixiong, who is also the witness of his first murder...

a book about how kindness can change the path of fate, often when you aren’t paying attention. also, an audiodrama about 锦鲤 letting loose asldkfajsdf

#6: 《默读》 Mo Du by priest

genre(s): crime fiction, detective fiction

mediums: original novel on JJWXC, audiodrama by 729声工厂 on 猫耳FM (currently banned), donghua and live action adaptations in progress that will never see the light of day because this book contains trenchant commentary about social issues and cycles of violence perpetuated by wealth and power (and therefore too transgressive for the censors rip)

ETA 12/23/22: the 《默读》 AD has returned! more of it has likely been censored, but I’ll take what we can get.

when a series of complex cases begins to shake Yan City, police inspector Luo Wenzhou must team up with Fei Du, the cryptic heir of a business empire, to uncover what may be a larger, decades-spanning conspiracy tying the crimes together. at the same time, a mysterious radio station releases reviews of classic novels in Western literature that all feature plots, events, themes, and crimes that bear uncanny resonances to the cases they are investigating. a book about the dark side of modern society, and the slow, grueling path out of the abyss and toward the light

#7: 《督主有病》 Du Zhu You Bing by 杨溯 Yang Su

genre(s): wuxia, political intrigue

mediums: original novel on 长佩 Changpei, audiodrama by 米波文化 Mibo Culture on 猫耳FM

the unlikely childhood friendship of a court official and an assassin must weather the rise and fall of regimes as well as grasping reach of their own backgrounds if they are to reach a distant, elusive happy ending. a book where the question “can things get worse?” is responded to with a hearty “always!” 

#8: 《海中爵》 Hai Zhong Jue by 七药 Qi Yao (full crash course here)

genre(s): PIRATES, secondary world fantasy, political intrigue

mediums: original novel on 长佩 Changpei, (free!) audiodrama by 株木琅玛工作室 Zhumulangma Studio on 猫耳FM, audiodrama ongoing

when a smooth-talking, deep-pocketed rival ship’s captain offers him a deal he can’t refuse, Hailian reluctantly agrees to assassinate someone for the mysterious Fang Tinglan. drawn into the complex tangle of Fang Tinglan’s schemes, Hailian must navigate intrigue, betrayal, and his own lost past to find his way to some place he can call home. a book about fighting and falling in love at the same time

#9: 《哏儿》 Gen’er by 南北逐风 Nan Bei Zhu Feng

genre(s): contemporary, entertainment industry

mediums: original novel on 长佩 Changpei, audiodrama by 音熊联萌 VoiceBear Alliance on 猫耳FM

in a few days, Ye Ling will graduate from the illustrious Tsinghua University with a master’s degree in thermal engineering, so in a few days, he’ll no longer have the time to pursue his extracurricular dreams of performing 相声 xiangsheng / crosstalk, a form of traditional Chinese stand-up comedy. but when the brash, bold, and charismatic Xie Shuangchen barges into his life, Ye Ling’s heart is swayed — and what if he decides to pursue his dreams? what if this is what he’s meant to do? a book about making it as working artists in Beijing while falling in love. also book about 相声 xiangsheng and Chinese opera, and adapting classical forms to the modern era

#10: 《杀破狼》 Sha Po Lang by priest

genre(s): political intrigue, alternate history, steampunk wuxia

mediums: original novel on JJWXC, audiodrama by 729声工厂 on 猫耳FM, live action adaptation trapped in censorship hell

from the moment the powerful fuel 紫流金 ziliujin was dug out of the ground, the path of history was destined to change. in an aging and weakening Liang Dynasty, two young men come of age as the kingdom’s foremost general and the court’s most capable minister. but malevolent forces both external and internal, domestic and foreign threaten to destroy them before they can save the dynasty they inherited. a book about saving your kingdom while extremely burnt out by the traumatic events of your youth. also, steampunk mechas and navigating the industrial revolution in the middle of war

#11: 《金牌助理之弯弯没想到》 Jin Pai Zhu Li zhi Wan Wan Mei Xiang Dao by (ostensibly) 非天夜翔 Fei Tian Ye Xiang and (mostly) 传奇火箭队 The Legendary Rocket Team, aka Fuck the Rocket according to their subtitles

genre(s): contemporary, entertainment industry

mediums: original novel on JJWXC, (free!) audiodrama by the 传奇火箭队 The Legendary Rocket Team on 猫耳FM

so full disclosure, I never read the original novel, and the 《弯弯》 audiodrama should be considered a lot of things but a faithful adaptation? lol absolutely not (their own words)

this is actually a 网配 wangpei audiodrama from 2015, and the energy on it is utterly unhinged. it is simultaneously a love letter to and satire of 非天夜翔 Fei Tian Ye Xiang’s novel 《金牌助理》 Jin Pai Zhu Li, a novel that follows the misadventures of hapless aspiring musician Xiao Yi as he finds a day job to pay the bills while struggling to make it in Beijing. said day job? working as a personal assistant to the extremely frosty, extremely handsome superstar actor Lu Zhou. absolute hijinks ensue

this audiodrama is far ahead of its time, and also completely upends traditional adaptation by rewriting the script satirically and cranking up the speed. I screamed; I laughed; I definitely missed a turn while driving. words can’t really describe this production for its sheer insanity, so I’ll just link it above and call it a day

[shookethdev]

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NAKU 🫵

[kneedeepincynade]

A little step toward a better world has just been achieved today,as the communists form a government in Nepal openly challenging Indian imperialism and the buthan puppet government

The post is machine translated

The translation is at the bottom

The collective is on telegram

⚠️ IL NEPAL AVRÀ UN GOVERNO COMUNISTA, VITTORIA GEOPOLITICA PER IL PARTITO COMUNISTA CINESE ⚠️

🇨🇳|🇳🇵 Il 12 settembre, Li Zhanshu - Presidente del Comitato Permanente dell'Assemblea Nazionale del Popolo Cinese - si è recato in Nepal, per un incontro sia con Bidhya Devi Bhandari - Presidente del Nepal - che con i vertici dei due partiti comunisti:

🔺CPN-UML - il cui Segretario è Khadga Prasad Sharma Oli 🚩

https://www.cpnuml.org/

🔺CPN-MC - il cui Segretario Generale è Dev Gurung, ma la figura più importante del partito è Pushpa Kamal Dahal, conosciuta come "Prachanda", un ex-guerrigliero maoista 🚩

https://www.cpnmc.org/

✈️ Si trattava, al tempo, della terza Visita di Alto Livello di un membro del Partito Comunista Cinese in Nepal, dopo quella di Wang Yi - Ministro degli Affari Esteri della RPC, e Liu Jinchao - Direttore del Dipartimento degli Affari Esteri del Comitato Centrale del Partito Comunista Cinese, che si occupa delle relazioni tra il CPC e partiti politici esteri, come il Partito Comunista del Vietnam o il Partito Rivoluzionario del Popolo Lao ⭐️

🧾 Il 20 novembre, in un clima "bollente", si sono svolte le elezioni in Nepal, e le formazioni si sono presentate in questo modo:

📄 La "Coalizione dei 5 Partiti", una sorta di miscuglio - essenzialmente guidato dall'opportunismo - che aveva iniziato a guidare il paese dopo il litigio tra Oli e Prachanda nel 2020. In tale coalizione, che presentava i medesimi partiti della coalizione di governo, vi era il Partito del Congresso, un partito politico pro-India e pro-USA, così come l'MC di Prachanda (❗️), che si trovava lì per motivi opportunistici più che ideologici.

📄 L'UML - guidato da Khadga Prasad Sharma Oli - come unico partito d'opposizione.

📊 Le elezioni in Nepal si dividono in "Party List" e "Constituency" - l'UML aveva preso 26,95% nel PL e 30,83% nel Constituency, mentre il Congresso 25,71% e 23,19%, e l'MC 11,13% e 9,37%.

🏵 Alle elezioni, l'UML ha trionfato in quasi tutte le regioni, ma la C5P - se unita - superava di gran lunga l'UML, anche se mancavano due seggi per l'ottenimento della maggioranza.

🇮🇳|🇺🇸 In ogni caso, sembrava fatta per una vittoria di una coalizione pro-India e pro-USA guidata dal Partito del Congresso, che aveva in mente di accettare un pacchetto da 500 milioni di dollari dagli USA, un vero e proprio "acquisto di sovranità" da parte degli imperialisti statunitensi, che avevano intenzione di trasformare il Nepal nell'ennesimo fantoccio anti-Cinese e anti-comunista.

↩️ Invece, nei giorni precedenti, Prachanda - leader dell'MC - ha iniziato a mostrare un dissapore nei confronti della C5P, rea - secondo lui - di aver tradito le promesse pre-elezioni.

https://www.washingtonpost.com/world/2022/12/26/maoist-leader-prachanda-emerges-nepals-next-prime-minister/

⭐️ Inoltre, Dev Gurung - SG del Centro Maoista - ha iniziato a proporre l'idea di una coalizione comunista, e così, sia lui che Prachanda, hanno iniziato a dialogare con Khadga Prasad Sharma Oli 🚩

🇨🇳 Wang Xin - Ambasciatore Cinese in Nepal - ha intensificato gli incontri politici con i partiti comunisti del Nepal, con l'obiettivo di costruire l'unità per poter governare.

🇳🇵Inoltre, Barsaman Pun - membro del Centro Maoista, ed ex guerrigliero - è tornato velocemente in Nepal dalla Cina, per contribuire - come affermato da Khabarhub, media nepalese - alla costruzione dell'unità tra i comunisti.

🇳🇵E così, nonostante le alte probabilità di un nuovo governo pro-India e pro-USA, ieri - 25 dicembre - è stata annunciata l'alleanza tra i comunisti, tra l'UML e il MC, con Pushpa Kamal Dahal - Prachanda - come nuovo Primo Ministro.

🇳🇵|🇮🇳|🇨🇳 Il Nepal è da sempre in orbita pro-India, pertanto un tale capovolgimento - il secondo, per giunta, ma questa volta dovrebbe essere più stabile - rappresenta un'enorme vittoria geopolitica, nonché ideologica, del Partito Comunista Cinese.

🌸 Iscriviti 👉 @collettivoshaoshan

⚠️ NEPAL WILL HAVE A COMMUNIST GOVERNMENT, GEOPOLITIC VICTORY FOR THE COMMUNIST PARTY OF CHINA ⚠️

🇨🇳|🇳🇵 On September 12, Li Zhanshu - Chairman of the Standing Committee of the National People's Congress of China - went to Nepal, for a meeting with both Bidhya Devi Bhandari - President of Nepal - and with the leaders of the two parties communists:

🔺CPN-UML - whose Secretary is Khadga Prasad Sharma Oli 🚩

https://www.cpnuml.org/

🔺CPN-MC - whose General Secretary is Dev Gurung, but the most important figure of the party is Pushpa Kamal Dahal, known as "Prachanda", an ex-Maoist guerrilla 🚩

https://www.cpnmc.org/

✈️ It was, at the time, the third High-Level Visit of a member of the Communist Party of China to Nepal, after that of Wang Yi - Minister of Foreign Affairs of the PRC, and Liu Jinchao - Director of the Foreign Affairs Department of the Central Committee of the Communist Party of China, which deals with the relationship between the CPC and foreign political parties, such as the Communist Party of Vietnam or the Lao People's Revolutionary Party ⭐️

🧾 On November 20, in a "hot" climate, elections were held in Nepal, and the formations presented themselves as follows:

📄 The "Coalition of 5 Parties", a sort of hodgepodge - essentially driven by opportunism - which had started to lead the country after the quarrel between Oli and Prachanda in 2020. In this coalition, which featured the same parties as the government coalition , there was the Congress Party, a pro-India and pro-US political party, as well as Prachanda's MC (❗️), who were there for opportunistic rather than ideological reasons.

📄 The UML - led by Khadga Prasad Sharma Oli - as the only opposition party.

📊 Elections in Nepal are divided into "Party List" and "Constituency" - the UML had taken 26.95% in the PL and 30.83% in the Constituency, while the Congress 25.71% and 23.19%, and the MC 11.13% and 9.37%.

🏵 In the elections, the UML triumphed in almost all regions, but the C5P - if united - far exceeded the UML, even if there were two seats left to obtain a majority.

🇮🇳|🇺🇸 In any case, it seemed made for a victory of a pro-India and pro-US coalition led by the Congress Party, which was planning to accept a 500 million dollar package from the US, a real "buying of sovereignty" by the US imperialists, who intended to turn Nepal into yet another anti-Chinese and anti-communist puppet.

↩️ Instead, in the previous days, Prachanda - leader of the MC - began to show a disagreement with the C5P, guilty - according to him - of having betrayed the pre-election promises.

https://www.washingtonpost.com/world/2022/12/26/maoist-leader-prachanda-emerges-nepals-next-prime-minister/

⭐️ Also, Dev Gurung - SG of Maoist Center - started proposing the idea of ​​communist coalition, and so both he and Prachanda started dialogue with Khadga Prasad Sharma Oli 🚩

🇨🇳 Wang Xin - Chinese Ambassador in Nepal - has intensified political meetings with the communist parties of Nepal, with the aim of building unity in order to govern.

🇳🇵 Furthermore, Barsaman Pun - a member of the Maoist Center, and a former guerrilla - quickly returned to Nepal from China, to contribute - as stated by Khabarhub, Nepalese media - to the construction of unity among the communists.

🇳🇵And so, despite the high probability of a new pro-India and pro-USA government, yesterday - December 25th - the alliance between the communists, between the UML and the MC, with Pushpa Kamal Dahal - Prachanda was announced - as the new Prime Minister.

🇳🇵|🇮🇳|🇨🇳 Nepal has always been in a pro-India orbit, therefore such a reversal - the second, moreover, but this time should be more stable - represents a huge geopolitical, as well as ideological, victory for the Party Chinese Communist.

🌸 Subscribe 👉 @collettivoshaoshan

[eyenaku]

Ji ji fu ji ji

a o e i i er ai ei ao ou an en ang eng ong i ia iao ie iu ian in iang ing iong u ua uo uai ui uan un uang ueng ü üe üan ün a o e er ai ao ou an en ang eng yi ya yao ye you yan yin yang ying yong wu wa wo wai wei wan wen wang weng yu yue yuan yun b ba bo bai bei bao ban ben bang beng bi biao bie bian bin bing bu p pa po pai pei pao pou pan pen pang peng pi piao pie pian pin ping pu m ma mo me mai mei mao mou man men mang meng mi miao mie miu mian min ming mu f fa fo fei fou fan fen fang feng fu d da de dai dei dao dou dan den dang deng dong di diao die diu dian ding du duo dui duan dun t ta te tai tei tao tou tan tang teng tong ti tiao tie tian ting tu tuo tui tuan tun n na ne nai nei nao nou nan nen nang neng nong ni niao nie niu nian nin niang ning nu nuo nuan nü nüe l la le lai lei lao lou lan lang leng long li lia liao lie liu lian lin liang ling lu luo luan lun lü lüe g ga ge gai gei gao gou gan gen gang geng gong gu gua guo guai gui guan gun guang k ka ke kai kei kao kou kan ken kang keng kong ku kua kuo kuai kui kuan kun kuang h ha he hai hei hao hou han hen hang heng hong hu hua huo huai hui huan hun huang z za ze zi zai zei zao zou zan zen zang zeng zong zu zuo zui zuan zun c ca ce ci cai cao cou can cen cang ceng cong cu cuo cui cuan cun s sa se si sai sao sou san sen sang seng song su suo sui suan sun zh zha zhe zhi zhai zhei zhao zhou zhan zhen zhang zheng zhong zhu zhua zhuo zhuai zhui zhuan zhun zhuang ch cha che chi chai chao chou chan chen chang cheng chong chu chua chuo chuai chui chuan chun chuang sh sha she shi shai shei shao shou shan shen shang sheng shu shua shuo shuai shui shuan shun shuang r re ri rao rou ran ren rang reng rong ru rua ruo rui ruan run j ji jia jiao jie jiu jian jin jiang jing jiong ju jue juan jun q qi qia qiao qie qiu qian qin qiang qing qiong qu que quan qun x xi xia xiao xie xiu xian xin xiang xing xiong xu xue xuan xun

[jcmarchi]

Google at NeurIPS 2023

New Post has been published on https://thedigitalinsider.com/google-at-neurips-2023/

Google at NeurIPS 2023

This week the 37th annual Conference on Neural Information Processing Systems (NeurIPS 2023), the biggest machine learning conference of the year, kicks off in New Orleans, LA. Google is proud to be a Diamond Level sponsor of NeurIPS this year and will have a strong presence with >170 accepted papers, two keynote talks, and additional contributions to the broader research community through organizational support and involvement in >20 workshops and tutorials. Google is also proud to be a Platinum Sponsor for both the Women in Machine Learning and LatinX in AI workshops. We look forward to sharing some of our extensive ML research and expanding our partnership with the broader ML research community.

Attending for NeurIPS 2023 in person? Come visit the Google Research booth to learn more about the exciting work we’re doing to solve some of the field’s most interesting challenges. Visit the @GoogleAI X (Twitter) account to find out about Google booth activities (e.g., demos and Q&A sessions).

You can learn more about our latest cutting edge work being presented at the conference in the list below (Google affiliations highlighted in bold). And see Google DeepMind’s blog to learn more about their participation at NeurIPS 2023.

Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization Adel Javanmard, Vahab Mirrokni

Better Private Linear Regression Through Better Private Feature Selection Travis Dick, Jennifer Gillenwater*, Matthew Joseph

Binarized Neural Machine Translation Yichi Zhang, Ankush Garg, Yuan Cao, Łukasz Lew, Behrooz Ghorbani*, Zhiru Zhang, Orhan Firat

BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran

Boosting with Tempered Exponential Measures Richard Nock, Ehsan Amid, Manfred Warmuth

Concept Algebra for (Score-Based) Text-Controlled Generative Models Zihao Wang, Lin Gui, Jeffrey Negrea, Victor Veitch

Deep Contract Design via Discontinuous Networks Tonghan Wang, Paul Dütting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes

Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection Cheng-Ju Ho, Chen-Hsuan Tai, Yen-Yu Lin, Ming-Hsuan Yang, Yi-Hsuan Tsai

Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew Walter

Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy Anastasia Koloskova*, Ryan McKenna, Zachary Charles, J Keith Rush, Hugh Brendan McMahan

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products Tamas Sarlos, Xingyou Song, David P. Woodruff, Qiuyi (Richard) Zhang

Module-wise Adaptive Distillation for Multimodality Foundation Models

Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou

Multi-Swap k-Means++ Lorenzo Beretta, Vincent Cohen-Addad, Silvio Lattanzi, Nikos Parotsidis

OpenMask3D: Open-Vocabulary 3D Instance Segmentation Ayça Takmaz, Elisabetta Fedele, Robert Sumner, Marc Pollefeys, Federico Tombari, Francis Engelmann

Order Matters in the Presence of Dataset Imbalance for Multilingual Learning Dami Choi*, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M. Dai, Behrooz Ghorbani

PopSign ASL v1.0: An Isolated American Sign Language Dataset Collected via Smartphones Thad Starner, Sean Forbes, Matthew So, David Martin, Rohit Sridhar, Gururaj Deshpande, Sam Sepah, Sahir Shahryar, Khushi Bhardwaj, Tyler Kwok, Daksh Sehgal, Saad Hassan, Bill Neubauer, Sofia Vempala, Alec Tan, Jocelyn Heath, Unnathi Kumar, Priyanka Mosur, Tavenner Hall, Rajandeep Singh, Christopher Cui, Glenn Cameron, Sohier Dane, Garrett Tanzer

Semi-Implicit Denoising Diffusion Models (SIDDMs) Yanwu Xu*, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou

State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding Devleena Das, Sonia Chernova, Been Kim

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization Emanuele Bugliarello*, Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender

Subject-driven Text-to-Image Generation via Apprenticeship Learning Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, William W. Cohen

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao*, Bahare Fatemi, Mike Burrows, Charith Mendis*, Bryan Perozzi

Training Chain-of-Thought via Latent-Variable Inference Du Phan, Matthew D. Hoffman, David Dohan*, Sholto Douglas, Tuan Anh Le, Aaron Parisi, Pavel Sountsov, Charles Sutton, Sharad Vikram, Rif A. Saurous

Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints Jayadev Acharya, Clement L. Canonne, Ziteng Sun, Himanshu Tyagi

What You See is What You Read? Improving Text-Image Alignment Evaluation Michal Yarom, Yonatan Bitton, Soravit Changpinyo, Roee Aharoni, Jonathan Herzig, Oran Lang, Eran Ofek, Idan Szpektor

When Does Confidence-Based Cascade Deferral Suffice? Wittawat Jitkrittum, Neha Gupta, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sanjiv Kumar

Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekström Kelvinius, Dimitar Georgiev, Artur Petrov Toshev, Johannes Gasteiger

AVIS: Autonomous Visual Information Seeking with Large Language Model Agent Ziniu Hu*, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, David Ross, Cordelia Schmid, Alireza Fathi

Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing “Spurious” Correlations Qingyao Sun, Kevin Patrick Murphy, Sayna Ebrahimi, Alexander D’Amour

Collaborative Score Distillation for Consistent Visual Editing Subin Kim, Kyungmin Lee, June Suk Choi, Jongheon Jeong, Kihyuk Sohn, Jinwoo Shin

CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam

Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy Amit Daniely, Nathan Srebro, Gal Vardi

A Computationally Efficient Sparsified Online Newton Method Fnu Devvrit*, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S Dhillon

DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field Chenyangguang Zhang, Yan Di, Ruida Zhang, Guangyao Zhai, Fabian Manhardt, Federico Tombari, Xiangyang Ji

Double Auctions with Two-sided Bandit Feedback Soumya Basu, Abishek Sankararaman

Grammar Prompting for Domain-Specific Language Generation with Large Language Models Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim

Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training Rie Johnson, Tong Zhang*

Large Graph Property Prediction via Graph Segment Training Kaidi Cao*, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis*, Jure Leskovec, Bryan Perozzi

On Computing Pairwise Statistics with Local Differential Privacy Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

On Student-teacher Deviations in Distillation: Does it Pay to Disobey? Vaishnavh Nagarajan, Aditya Krishna Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar

Optimal Cross-learning for Contextual Bandits with Unknown Context Distributions Jon Schneider, Julian Zimmert

Near-Optimal k-Clustering in the Sliding Window Model David Woodruff, Peilin Zhong, Samson Zhou

Post Hoc Explanations of Language Models Can Improve Language Models Satyapriya Krishna, Jiaqi Ma, Dylan Z Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju

Recommender Systems with Generative Retrieval Shashank Rajput*, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy

Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh*, Kangwook Lee, Kimin Lee*

Replicable Clustering Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou

Replicability in Reinforcement Learning Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou

Riemannian Projection-free Online Learning Zihao Hu, Guanghui Wang, Jacob Abernethy

Sharpness-Aware Minimization Leads to Low-Rank Features Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank Reddi, Tengyu Ma, Stefanie Jegelka

Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S Dhillon, Cho-Jui Hsieh

Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain

Boundary Guided Learning-Free Semantic Control with Diffusion Models Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du*, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang

Conformal Prediction for Time Series with Modern Hopfield Networks Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter

Does Visual Pretraining Help End-to-End Reasoning? Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, Cordelia Schmid

Effective Robustness Against Natural Distribution Shifts for Models with Different Training Data Zhouxing Shi*, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel*, Yao Qin

Improving Neural Network Representations Using Human Similarity Judgments Lukas Muttenthaler*, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine Hermann, Andrew K. Lampinen, Simon Kornblith

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala

Mnemosyne: Learning to Train Transformers with Transformers Deepali Jain, Krzysztof Choromanski, Avinava Dubey, Sumeet Singh, Vikas Sindhwani, Tingnan Zhang, Jie Tan

Nash Regret Guarantees for Linear Bandits Ayush Sawarni, Soumyabrata Pal, Siddharth Barman

A Near-Linear Time Algorithm for the Chamfer Distance Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten.

On Differentially Private Sampling from Gaussian and Product Distributions Badih Ghazi, Xiao Hu*, Ravi Kumar, Pasin Manurangsi

On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes Jia Lin Hau, Erick Delage, Mohammad Ghavamzadeh*, Marek Petrik

ResMem: Learn What You Can and Memorize the Rest Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar

Responsible AI (RAI) Games and Ensembles Yash Gupta, Runtian Zhai, Arun Suggala, Pradeep Ravikumar

RoboCLIP: One Demonstration Is Enough to Learn Robot Policies Sumedh A Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti

Robust Concept Erasure via Kernelized Rate-Distortion Maximization Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao

Simplicity Bias in 1-Hidden Layer Neural Networks Depen Morwani*, Jatin Batra, Prateek Jain, Praneeth Netrapalli

SLaM: Student-Label Mixing for Distillation with Unlabeled Examples Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee

SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding Paul-Edouard Sarlin*, Eduard Trulls, Marc Pollefeys, Jan Hosang, Simon Lynen

SOAR: Improved Indexing for Approximate Nearest Neighbor Search Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar

StyleDrop: Text-to-Image Synthesis of Any Style Kihyuk Sohn, Lu Jiang, Jarred Barber, Kimin Lee*, Nataniel Ruiz, Dilip Krishnan, Huiwen Chang*, Yuanzhen Li, Irfan Essa, Michael Rubinstein, Yuan Hao, Glenn Entis, Irina Blok, Daniel Castro Chin

Three Towers: Flexible Contrastive Learning with Pretrained Image Models Jannik Kossen*, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

Two-Stage Learning to Defer with Multiple Experts Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong

AdANNS: A Framework for Adaptive Semantic Search Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham Kakade, Prateek Jain, Ali Farhadi

Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer Bowen Tan*, Yun Zhu, Lijuan Liu, Eric Xing, Zhiting Hu, Jindong Chen

Causal-structure Driven Augmentations for Text OOD Generalization Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David Blei

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell

Diffusion Self-Guidance for Controllable Image Generation Dave Epstein, Allan Jabri, Ben Poole, Alexei A Efros, Aleksander Holynski

Fully Dynamic k-Clustering in Õ(k) Update Time Sayan Bhattacharya, Martin Nicolas Costa, Silvio Lattanzi, Nikos Parotsidis

Improving CLIP Training with Language Rewrites Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian

<!–k-Means Clustering with Distance-Based Privacy Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong

–>

LayoutGPT: Compositional Visual Planning and Generation with Large Language Models Weixi Feng, Wanrong Zhu, Tsu-Jui Fu, Varun Jampani, Arjun Reddy Akula, Xuehai He, Sugato Basu, Xin Eric Wang, William Yang Wang

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management Dhawal Gupta*, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh*, Craig Boutilier

Optimal Unbiased Randomizers for Regression with Label Differential Privacy Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Jacob Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang

Paraphrasing Evades Detectors of AI-generated Text, but Retrieval Is an Effective Defense Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, Mohit Iyyer

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation Shuyang Sun*, Weijun Wang, Qihang Yu*, Andrew Howard, Philip Torr, Liang-Chieh Chen*

Robust and Actively Secure Serverless Collaborative Learning Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang

SpecTr: Fast Speculative Decoding via Optimal Transport Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix Yu

Structured Prediction with Stronger Consistency Guarantees Anqi Mao, Mehryar Mohri, Yutao Zhong

Affinity-Aware Graph Networks Ameya Velingker, Ali Kemal Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi

ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections Chun-Han Yao*, Amit Raj, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani

Black-Box Differential Privacy for Interactive ML Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer

Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits Haolin Liu, Chen-Yu Wei, Julian Zimmert

DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model

Xiuye Gu, Yin Cui*, Jonathan Huang, Abdullah Rashwan, Xuan Yang, Xingyi Zhou, Golnaz Ghiasi, Weicheng Kuo, Huizhong Chen, Liang-Chieh Chen*, David Ross

Easy Learning from Label Proportions Robert Busa-Fekete, Heejin Choi*, Travis Dick, Claudio Gentile, Andres Munoz Medina

Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish Tendulkar, Rishabh Iyer, Abir De

Faster Differentially Private Convex Optimization via Second-Order Methods Arun Ganesh, Mahdi Haghifam*, Thomas Steinke, Abhradeep Guha Thakurta

Finding Safe Zones of Markov Decision Processes Policies Lee Cohen, Yishay Mansour, Michal Moshkovitz

Focused Transformer: Contrastive Training for Context Scaling Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu*, Henryk Michalewski, Piotr Miłoś

Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

H-Consistency Bounds: Characterization and Extensions Anqi Mao, Mehryar Mohri, Yutao Zhong

Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation David Brandfonbrener, Ofir Nachum, Joan Bruna

Most Neural Networks Are Almost Learnable Amit Daniely, Nathan Srebro, Gal Vardi

Multiclass Boosting: Simple and Intuitive Weak Learning Criteria Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran

NeRF Revisited: Fixing Quadrature Instability in Volume Rendering Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Krishna Thomas, Leonidas Guibas, Ke Li

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Wei-Ning Chen, Dan Song, Ayfer Ozgur, Peter Kairouz

Private Federated Frequency Estimation: Adapting to the Hardness of the Instance Jingfeng Wu*, Wennan Zhu, Peter Kairouz, Vladimir Braverman

RETVec: Resilient and Efficient Text Vectorizer Elie Bursztein, Marina Zhang, Owen Skipper Vallis, Xinyu Jia, Alexey Kurakin

Symbolic Discovery of Optimization Algorithms Xiangning Chen*, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le

A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa F. Polania, Varun Jampani, Deqing Sun, Ming-Hsuan Yang

A Trichotomy for Transductive Online Learning Steve Hanneke, Shay Moran, Jonathan Shafer

A Unified Fast Gradient Clipping Framework for DP-SGD William Kong, Andres Munoz Medina

Unleashing the Power of Randomization in Auditing Differentially Private ML Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh

(Amplified) Banded Matrix Factorization: A unified approach to private training Christopher A Choquette-Choo, Arun Ganesh, Ryan McKenna, H Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta, Zheng Xu

Adversarial Resilience in Sequential Prediction via Abstention Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty

Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception Hassan Akbari, Dan Kondratyuk, Yin Cui, Rachel Hornung, Huisheng Wang, Hartwig Adam

Android in the Wild: A Large-Scale Dataset for Android Device Control Christopher Rawles, Alice Li, Daniel Rodriguez, Oriana Riva, Timothy Lillicrap

Benchmarking Robustness to Adversarial Image Obfuscations Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal

Building Socio-culturally Inclusive Stereotype Resources with Community Engagement Sunipa Dev, Jaya Goyal, Dinesh Tewari, Shachi Dave, Vinodkumar Prabhakaran

Consensus and Subjectivity of Skin Tone Annotation for ML Fairness Candice Schumann, Gbolahan O Olanubi, Auriel Wright, Ellis Monk Jr*, Courtney Heldreth, Susanna Ricco

Counting Distinct Elements Under Person-Level Differential Privacy Alexander Knop, Thomas Steinke

DICES Dataset: Diversity in Conversational AI Evaluation for Safety Lora Aroyo, Alex S. Taylor, Mark Diaz, Christopher M. Homan, Alicia Parrish, Greg Serapio-García, Vinodkumar Prabhakaran, Ding Wang

Does Progress on ImageNet Transfer to Real-world Datasets? Alex Fang, Simon Kornblith, Ludwig Schmidt

Estimating Generic 3D Room Structures from 2D Annotations Denys Rozumnyi*, Stefan Popov, Kevis-kokitsi Maninis, Matthias Nießner, Vittorio Ferrari

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset Sneha Kudugunta, Isaac Caswell, Biao Zhang, Xavier Garcia, Derrick Xin, Aditya Kusupati, Romi Stella, Ankur Bapna, Orhan Firat

Mechanic: A Learning Rate Tuner Ashok Cutkosky, Aaron Defazio, Harsh Mehta

NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations Varun Jampani, Kevis-kokitsi Maninis, Andreas Engelhardt, Arjun Karpur, Karen Truong, Kyle Sargent, Stefan Popov, Andre Araujo, Ricardo Martin Brualla, Kaushal Patel, Daniel Vlasic, Vittorio Ferrari, Ameesh Makadia, Ce Liu*, Yuanzhen Li, Howard Zhou

Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Nunez, James Lottes, Qing Wang, Yi-Fan Chen, John Roberts Anderson, Fei Sha

Restart Sampling for Improving Generative Processes Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi Jaakkola

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko

RoboHive: A Unified Framework for Robot Learning Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran

SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi, Hugo Larochelle, David Rolnick

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YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus Dave Uthus, Garrett Tanzer, Manfred Georg

The Noise Level in Linear Regression with Dependent Data Ingvar Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

[siumerghe]

The lineage of the Tang imperial house and its problems

By the time of the Sui-Tang era, a person’s culture played a more important role than his race. The ethnic origin of the Yang (楊) clan of the Sui and the Li clan of the Tang did not have much to do with their policies. They might well have descended from prominent Han families, but it is certain that these clans, a few generations back from the dynastic founders, had lived in the Wuchuan garrison, north of Yinshan (陰山) mountain for quite a long period of time. This historical fact seems to have given rise to the suspicion that the Sui and Tang imperial houses were of barbarian origin. 

The suspicion about the origin of the Li clan had existed from the very beginning of the dynasty, because they had once had the hu surname Daye (大野). The Buddhist monk Falin (法琳) declared before Taizong that the Tang imperial house originated from Xianbei Tuoba Dadu (達闍 i.e., Li in Chinese) which was a noble scion of Yinshan, i.e., a barbarian lineage. Although Taizong reprimanded Falin, during the war of unification an enemy, Dan Xiongxin (單雄信), called Taizong’s brother Yuanji (元吉) a hu child, and a Tang minister Sun Fuqie (孫伏伽) let slip that when Gaozu Li Yuan was a child his friends were all queue-haired because the royal family was deeply imbued with hu custom. 

The in-laws of the royal family were completely of the hu line. Li Yuan’s mother was a daughter of Dugu Xin (獨孤信), the Grand Marshal of the Northern Zhou, and a sister of Empress Dugu of Emperor Wen of the Sui, making Li Yuan nephew-in-law to Yang Jian (楊堅) and maternal cousin of Emperor Yang (煬帝). Li Yuan married the daughter of Dou Yi (竇毅), who was of the Xianbei line and a prefectural commander of the Sui. The mother of Empress Dou was the elder sister of Emperor Wu of the Northern Zhou, Senior Princess Xiangyang (襄陽長公主).

The lifestyles of Taizong and his crown prince Chengqian (承乾) were not much different from those of the hu people. During the incident of Xuanwu Gate (玄武門), Taizong killed his younger brother Yuanji and made Princess Yang, Yuanji’s wife, his own; Zhu Xi’s remark on this behavior is well known. Chengqian followed hu custom as well. He stole and slaughtered cattle and horses, and acted like a Turk qaghan, eating with his guards, wearing Turkic clothes, and speaking Turkic. 

During Zhenguan period when the Tang royal ancestral temple was being set up, the ministers were discussing who should be the progenitor, and Yu Zhining (于志寧) objected to the suggestion that it be Li Gao (李暠). If Li Gao was their true ancestor, why would the early Tang emperors not want the family of Li Bao of Longxi (隴西), who were descendants of Li Gao, included in the imperial clan lineage? And why did Gaozong further lower the family rank of Li Bao? Thus it has been argued that the ancestors of the Tang imperial house must have been a degraded household of the Lis of Zhaojun (趙郡), or had just borrowed the surname of Li of Zhaojun [Li of Zhaojun - one of the Four Great families of Shandong, very influential in the beginning of the Tang era]. Given the fact that Gaozong suppressed Li Bao and did not honor the lineage of Zhaojun Lis, it is most likely that the actual pedigree of the Tang imperial house was quite different from what it claimed to be and that it was ethnically non-Han Chinese.

The Tang was ruled by the Han people in name, but in reality was a multi-racial regime, so the Sui-Tang dynasty was still seen as a Xianbei state by the nomads of Eurasia or the people from the western regions, and Tang was called Taugas, Tamhaj, or Tabgaĉ which stood for Tuoba. The dynasties from the Dai (代) through Northern Wei and on to the Tang are separate according to the Chinese-style names for dynasties, but in fact form a continuous Tuoba state. Considering the continuity and commonality between these dynasties, placing them under the single heading of the Tuoba state seems appropriate. In this aspect, westerners from the fifth to the ninth century who called China Taugas, Tamhaj, or Tabgaĉ, were closer to the truth. Taizong’s acquisition of the title “Heavenly Qaghan” after the destruction of the Eastern Turks, Gaozong’s being addressed thus by nomadic rulers, and the fact that the majority of the early Sui-Tang imperial clan and high officials came from the military leaders of northern tribesmen, all provide further support to the Tuoba state argument.

Fabricating history and the rise of the zhonghua sovereign 

The imperial houses of Sui and Tang saw themselves as traditional Han Chinese, although they were genetically descendants of nomadic tribesmen such as the Xianbei and others. But no matter how they identified themselves and their dynasties, few saw them and their dynasties as purely Han Chinese. It is clear now that the Li house of the Tang did not descend from a renowned clan, even if they had been Han Chinese. 

Why then did the Tang imperial house want to fabricate a lineage to appear as if it had been one of the renowned Han aristocratic clans? Throughout Chinese history, a certain degree of sinicization has been necessary for anyone or anything alien to come to China and earn a place there. This was the case for Buddhism as well as Nestorian Christianity, but this did not mean they ceased to be Buddhism or Christianity. In addition to the issue of sinicization, the Wei-Jin-Northern and Southern Dynasties era was an age of pedigree. 

Chen Yinke (陳寅恪) has raised questions about Taizong’s re-publication of the History of the Jin and his ordering the writing of The Record of Clans and Lineages in the Zhenguan Reign Period (Zhenguan shizu zhi 貞觀氏族志), suggesting that the motive behind the omission, among the Sixteen Kingdoms, of Former Liang (��涼) and Western Liang (西涼) from the History of the Jin was the same as that behind The Record of Clans and Lineages in the Zhenguan Reign Period: namely to exalt the Li clan of the Tang and prove that they had a long and glorious pedigree. Many dynastic histories were written during Taizong’s reign; these were generally dynastic histories from after the era of the Three Kingdoms or from the History of the Jin, now re-written to conform to Tang legitimacy. The Tang imperial house strove to dispel the doubt that they originated from the Xianbei Tuoba tribe, and influenced the planning and compilation of dynastic histories, sometimes even down to the wording of the contents. 

First, let us look at the chronological records (zaiji 載記) of the History of the Jin. There are thirty chapters of chronological records in the book. The name originated from The Eastern Watch Records of the Han (Dongguan Hanji 東觀漢記), written by Ban Gu (班固) under order of Emperor Ming, and the number of thirty chapters seems to have been taken from the thirty chapters of biographies of feudal lords and eminent people (shijia 世家) in The Records of the Grand Historian. While the shijia is a record for each feudatory, the zaiji is a chronicle for the independent political entities in China which were not enfeoffed by the Chinese emperor. By including the Sixteen Kingdoms with the zaiji, Taizong set them in a different category and treated them as extraneous to the legitimate Jin dynasty, clearly taking the Han Chinese attitude of degrading alien regimes. 

The source for Taizong’s History of the Jin was The Spring and Autumn Annals of the Sixteen Kingdoms by Cui Hong of the Northern Wei, and in this book one record was devoted to each state; notably, though, two states which were recorded in the Annals were omitted in the zaiji of the History of the Jin. They are Former Liang (301–76), which was established by a Han Chinese, Zhang Gui (張軌) of Anding (安定), and which occupied the Hexi corridor (河西回廊), and Western Liang (400–421) which was established by Li Gao of Longxi. The latter was the person later manipulated to become the ancestor of the Tang imperial house, and omitting him and his state was surely Taizong’s intention. 

Another example is the compilation of the History of the Southern Dynasties (南史) and the History of the Northern Dynasties (北史), which concealed two underlying intentions. The first was to tie the Southern Dynasties (南朝) and Northern Dynasties (北朝) into one term, the Southern and Northern Dynasties (南北朝). If Taizong had truly been in favor of the Han Chinese point of view, he could have given legitimacy to the Southern Dynasties; but he could not ignore his own racial origins in the Northern Dynasties, and thus merging the two was the better option. Second, by including the Sui dynasty, the unifier of China, among the Northern Dynasties, he wanted to minimize the credit they received for having accomplished that unification. 

Many histories were published in the early Tang. Taizong’s reign saw the compilation of the so-called History of the Five Dynasties, namely History of the Liang, History of the Chen, History of the Northern Qi, History of the Zhou, History of the Sui, and in 646 History of the Jin (these six historical works are known as the Six Histories). Then, during Gaozong’s reign, still under the shadow of Taizong, the History of the Southern Dynasties and the History of the Northern Dynasties were completed. Among the twenty-four histories that are considered official dynastic histories, eight—a third of the total—were published at this time. Taizong had opened up a new era in Chinese history publication by beginning the tradition of government-sponsored official history, and also by permitting the incumbent emperor to inspect the records about himself, something that had previously been forbidden, and giving instructions on how to write about the incident of Xuanwu Gate.

Taizong’s manipulation of history was along the same lines as Gao Huan (高歡) of the Northern Qi, who distorted history and transformed his family into the renowned Bohai Gao clan; but it was successful. Tang monarchs managed to transform themselves from racially and culturally hu rulers into zhonghua emperors to such an extent that people of later times accept without doubt that the Tang was a legitimate Chinese dynasty. 

Taizong’s satisfaction with the effectiveness of official histories is manifest in the edict ordering the re-publication of History of the Jin: “How great is the usefulness of historical books!”

Source:  From Barbarians to the Middle Kingdom: The Rise of the Title “Emperor, Heavenly Qaghan” and Its Significance by Han-je Park http://cces.snu.ac.kr/data/publications/jces3_2park.pdf

[animesdoramasefilmesme]

Os melhores doramas(minha opinião)

Jardim de Meteoros

Atores: 

Shen Yue

Darren Chen

Caesar Wu 

Connor Leong

Annie Sun

Claire Dong

Runze Wang

Nicky Li

Dee Hsu

Liu Yin-Hao

Blake Abbie

Amber Kuo

Wang Lin

Dong Wang

Jin Haochen

Lidia Liu

Qian Sun

Dylan Wang

O que conta???

Essa linda historia romântica e muito engraçado conta de uma menina de 18 anos que se chama Shancai e e aceita em uma faculdade muito homenageada e conhece a F4 garotos herdeiros de grupos e muito ricos e gente para não ficar sem graça eu não vou falar o nome dos integrantes, mais e cheia de emoção , comedia , e muito romance.

Episódios:46 episódios,1 temporada

Onde pode assistir: Netflix, Rakuten Viki ou apps

Love Alarm

Atores:

Song Kang

Kim So-Hyun

Jung Ga Ram

Go Min Si

Shin Seung Ho 

Z. Hera 

Lee Jae Eung 

Song Seon-Mi

Song Geon Hee

Kim Si Eun 

Yong-Ok Kim

Cho Deok-Hoe

O que conta???

Essa historia e muito diferente trata de um aplicativo de romance que toca um alarme do celular da pessoa que você gosta, mais só se você estiver a 10 metros da pessoa ele conta a historia de uma garota que esta na escola e começa a namora e e obvio que vai ter o garoto rico que se apaixona pela mocinha mais então ele  tem um amigo que e pobre  e começa a gosta da garota principal.

Episódios: 8 episódios,1 temporada

onde pode assistir:Netflix, Rakuden Viki

Beleza Verdadeira

Atores:

Moon Ga Young

Park Yoo Na

Cha Eunwoo

Hwang Inyeop

Park Yoona

Im Semi

O que conta???

Bom eu sei que não coloquei muito atores mais não vamos falar disso então fala de uma garoto muito feia que e suada na escola e tem a garota má que e muito linda e essa garota a principal gosta de um cara da cantina então ela planeja se declarar mais a garota má  descobre e manipula o cara e fala para não aceita ai ele rejeita ela e a garota má faz um vídeo da rejeição ai ela muda de escola e começa usa maquiagem e tem medo de descobrir a sua faze de verdade.

Episódios:16 episódios, 1 temporada.

Onde pode assistir:Rakuden Viki.

Love020

Atores:

Mao Xiaotong

Bai Yu

Vin Zhang

Yang Yang

Zheng Shuang

Zheng Yecheng

Niu Junfeng

He Zhang

Chunrui Ma

Qin Yu

Liu Yinglun

Cui Hang

Denny Huang

Li Xinze

Yanqi Lu

Bian Cheng

Yujin Liu

Hu Haobo

Yiyi Long

Zhang Chaoren

Cai Gang

O que conta???

Essa historia romântica conta de uma menina linda inteligente e gamer ela e a segunda menina mais linda do campos e e claro que tem um gato nessa historia e também jogava o mesmo jogo que essa garota e ele pede ela em casamento no jogo e  tudo mais.

Episódios:30 episódios, 1 temporada

Onde pode assistir:Netflix,Rakuden Viki

Ombro Amigo

Atores:

Lin Yi

Xing Fei

Xiaotian Tang

Zhou Zi Xin

Yi Sha

Cai Gang

Zheng Ying

He Qiang

Liang Aiqi

Rong Rong

Gao Yu Fei

Zhou Junwei

O que conta???

E muito interessante essa historia de amor essa cara e lindo inteligente e muito famoso na faculdade e essa garota não e nada comparado a ele essa garota muda para um apartamento da amiga da sua mãe  a mãe tinha avisado que ele ia se muda para casa com ela e quando ele chega a casa esta todo bagunçado e suja e ela descobre que ele e famoso na faculdade e se  apaixona.

Episódios: 24 episódios, 1 temporada

Onde pode assistir:Netflix,RakudenViki

          OBRIGADO POR TER LIDO

😘🥰

[xiaolanhua]

The Love You Give Me 你给我的喜欢 (2023) – Episode 5

[lostinadrama]

𝐓𝐡𝐞 𝐋𝐨𝐯𝐞 𝐘𝐨𝐮 𝐆𝐢𝐯𝐞 𝐌𝐞 (2023)

[the-archlich]

"The system works." The first stage of Cao Pi's reign is literally putting down a coup attempt by Ding Yi and Bao Xun.

That’s a thing that never happened.

He did kill those guys but they never even tried to overthrow him. Ding Yi was a corrupt official who slandered Cui Yan and Mao Jie, and was one of Cao Zhi’s partisans. Bao Xin ended up as the rope in a nasty tug of war between Cao Pi and his ministers.

[exo-gr]

[200520] LAY: 玉 (Jade) pre-single from the 4th album

Stream / Buy: Youtube Music, iTunes, Spotify, Kuwo, KKBOX, friday, Naver Music, genie, FLO, melOn

DL: m4a

Lyrics:

(fan chang jie xuan zi jing ju 《ba wang bie ji》 xuan duan) M-m-m-murda Lay Do you know all the power that you hold baby My wrist is froze, they get blinded by the stones baby I need it To keep away the pain Stay with me everyday Do you feel the same (Oh baby yeah) She always know what I want like she's psychic You're a super hero baby let me be your side kick Ain't seen nothing like it Everything timeless They've been looking for it But I know where to find it yu yu yu yu yu yu mei ren bi ni zhen gui You zhi you wo dong de mei You But (n) nobody shine like yu yu yu yu yu yu And nobody shine like you I know you like diamonds too But (n) nobody shine like yu zhong bu tong ran hou jing ying ti tou zui zhen gui yu de mei yu zhong bu tong ran hou jing ying ti tou zui zhen gui ni de mei dong ni de ren you ren yi li zhi xin Baby ni de du te dong de ren cai you zi ge ban pei I need it you ni cai you wan mei jun zi fei ni bu zhui shen mi de fei cui wan mei de pei dui You belong by my side, keep you with me all the time I get lost in your eyes, but that's right where I reside With my woo You still make me nervous but it's cool That's my lil baby that's my woo She always know what I want like she's psychic You're a super hero baby let me be your side kick Ain't seen nothing like it Everything timeless They've been looking for it But I know where to find it yu yu yu yu yu yu mei ren bi ni zhen gui You zhi you wo dong de mei You But (n) nobody shine like (zi cong wo sui dai wang dong zheng xi zhan) yu yu yu yu yu yu And nobody shine like you I know you like diamonds too But (n) nobody shine like yu

[izayoi1242]

For China’s Overwhelmed Doctors, an Understanding Voice Across the Ocean

By BY ISABELLA KWAI Erjing Cui, a Seattle psychotherapist, volunteers for Yong Xin Kang Yi, a crisis line for medical workers fighting the coronavirus epidemic. Published: February 24, 2020 at 01:35PM from NYT World https://ift.tt/3c2jUER via IFTTT

[newsintheshell]

Kingdom, online un primo teaser per la terza stagione dell’anime

Svelati altri tre membri del cast della serie animata.

Diffuso un primo breve teaser trailer per l’attesa terza stagione di “Kingdom”, la serie animata tratta dal popolare manga di Yasuhisa Hara, edito in Italia da J-POP, che farà il suo ritorno dopo anni sulle tv giapponesi ad aprile, con alle spalle un nuovo staff.

Inoltre si aggiungono al cast:

Wu Feng Ming: Daisuke Namikawa

Xiang Yi: Tatsuhisa Suzuki

Bai Li: Yuto Uemura

La nuova stagione adatterà l’arco narrativo Gasshougun-hen raccontato dal volume numero 25 al 32 del manga ed è diretta da Kenichi Imaizumi (Katekyo Hitman Reborn!, Houkago Saikoro Club) presso Studio Signpost (precedentemente conosciuto come Pierrot Plus). La sceneggiatura è curata da Noboru Takagi (Altair: A Record of Battles, Golden Kamuy), mentre il character design è ad opera di Hisashi Abe (Berserk, Psycho-Pass: Sinners of the System).

Migliaia di anni sono passati dai tempi delle leggende, in cui il mondo degli uomini e quello degli dei erano così vicini da essere tutt'uno ed erano i sogni a cambiare la realtà . Erano i tempi della ‘Guerra dei 500 anni’, il periodo degli stati combattenti. Kingdom è la storia di un ragazzo di nome Xin, che si trasformò in un grande generale, e di tutte le prove che sostenne per afferrare il suo destino.

Hara ha lanciato l’opera sulle pagine di Weekly Young Jump nel 2006 e ad ora Shueisha ne ha pubblicato 55 volumi; l’autore ha affermato che sta considerando di proseguire fino a raggiungere i 100 numeri.

La prima stagione dell’anime prodotto da Studio Pierrot (Black Clover, Mr. Osomatsu), composta da 38 episodi, è andata in onda dal 2012 al 2013, seguita subito dopo da una seconda stagione di 39 puntate. Il manga ha anche ispirato un film live action, diretto da  Shinsuke Sato (già regista dei film con attori in carne ed ossa di Gantz, Death Note, Bleach e I am a Hero), uscito in Giappone lo scorso aprile.

Autore: SilenziO))) (@s1lenzi0)

[FONTE]