Stanford NLP Group @stanfordnlp
Computational Linguists—Natural Language—Machine Learning @chrmanning @jurafsky @percyliang @ChrisGPotts @tatsu_hashimoto @MonicaSLam @Diyi_Yang @StanfordAILab nlp.stanford.edu Stanford, CA, USA Joined February 2010-
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Generative Interfaces for Language Models doi.org/10.48550/arXiv… Jiaqi Chen, Yanzhe Zhang, Yutong Zhang, Yijia Shao, Diyi Yang （Stanford University） Large language models (LLMs) are increasingly seen as assistants, copilots, and consultants, capable of supporting a wide range…
Impressive work from @wen_kaiyue, @dlwh, @tengyuma & @percyliang! They did over 4.6k wandb runs to fairly benchmark 10 optimizers across 0.1B-1.2B. Matrix-based (Muon/Soap) lead, but gains shrink with scale. Check out their wandb workspace here: wandb.ai/marin-communit…
Impressive work from @wen_kaiyue, @dlwh, @tengyuma & @percyliang! They did over 4.6k wandb runs to fairly benchmark 10 optimizers across 0.1B-1.2B. Matrix-based (Muon/Soap) lead, but gains shrink with scale. Check out their wandb workspace here: wandb.ai/marin-communit…
A nice paper by @wen_kaiyue @dlwh @tengyuma @percyliang, doing the hard work of real comparison between optimizers. It's also very cool to see the first success come out of Stanford's Marin project!
A nice paper by @wen_kaiyue @dlwh @tengyuma @percyliang, doing the hard work of real comparison between optimizers. It's also very cool to see the first success come out of Stanford's Marin project!
Attended Yejin Choi's lecture yesterday on "Bending Scaling laws with Brighter Algorithms" and the 3 main drivers for this are Unconventional Data Unconventional Algorithms Unconventional Collaboration Some of the highlights of the talk (which I took notes) are below
Time Top 100 People in AI: Yejin Choi Professor, University of Washington time.com/collection/tim… #TIME100AI
How can the U.S. maintain a competitive edge on AI? It hinges on skilled talent, which means sustaining strong U.S. universities, said computer scientist @chrmanning. Read more insights from @StanfordHAI’s Congressional Boot Camp this year: hai.stanford.edu/news/ai-reshap…
(1/n) Check out our new paper: "Fantastic Pretraining Optimizers and Where to Find Them"! >4000 models to find the fastest optimizer! 2× speedups over AdamW? Unlikely. Beware under-tuned baseline or limited scale! E.g. Muon: ~40% speedups <0.5B & only 10% at 1.2B (8× Chinchilla)!
We did a very careful study of 10 optimizers with no horse in the race. Despite all the excitement about Muon, Mars, Kron, Soap, etc., at the end of the day, if you tune the hyperparameters rigorously and scale up, the speedup over AdamW diminishes to only 10% :-( Experiments…
We did a very careful study of 10 optimizers with no horse in the race. Despite all the excitement about Muon, Mars, Kron, Soap, etc., at the end of the day, if you tune the hyperparameters rigorously and scale up, the speedup over AdamW diminishes to only 10% :-( Experiments…
Both DSPy and (especially) GEPA are currently severely under hyped in the AI context engineering world
🎧 HELM goes audio! Announcing AHELM – a holistic evaluation of Audio-Language Models (ALMs) across 10 aspects. 📝 Paper: arxiv.org/abs/2508.21376 🥇 Leaderboard/prompts/raw predictions: crfm.stanford.edu/helm/audio/lat… See 🧵
this a very very nice course. i am currently doing assignment 1, having never coded a tokenizer before. plan is to work through entire course in a couple weeks.
this a very very nice course. i am currently doing assignment 1, having never coded a tokenizer before. plan is to work through entire course in a couple weeks.
FREE Natural Language Processing Course from Stanford. Link in comment. > 63 lectures covering everything from word representations and sentiment analysis to transformers, BERT, and neural information retrieval. > Perfect for mastering modern NLP techniques and building robust…
Connor has an incredible talent for explaining complex ideas in an accessible and practical way. In case you haven't watched this from last week.
Connor has an incredible talent for explaining complex ideas in an accessible and practical way. In case you haven't watched this from last week.
My first co-General Chair just got TIME100! Correlation or causation? You tell me ;) Congratulations @YejinChoinka!
My first co-General Chair just got TIME100! Correlation or causation? You tell me ;) Congratulations @YejinChoinka!
AI energy efficiency: the human brain as a model for smaller systems @Stanford Institute for Human-Centered Artificial Intelligence (HAI) new senior fellow Yejin Choi, named to TIME's 100 Most Influential People in AI in 2025, challenges the "bigger is better" narrative driving…
El cap 5 del libro de Martin & @jurafsky comienza con una cita a Zhuangzi ☯️ Las redes son para pescar; una vez que obtienes el pescado, puede olvidarte de la red. Las palabras son para dar significado; una vez que obtienes el significado, ya no necesitas las palabras.
Three folks that I believe deserve to be in the top 100 AI influencers from Time magazine. Congratulations! Of course, I've never heard of most of the other folks in that list! @hardmaru @YejinChoinka @elder_plinius
FREE NLP(Natural Language Processing) Course from Stanford. Link in comment. Covers everything from word vectors to transformers, LLMs like ChatGPT, and practical implementation with PyTorch. 23 lectures by Professor Christopher Manning.
Great opportunity for junior members of the community to share their work!
Great opportunity for junior members of the community to share their work!
A key challenge in human-AI collaboration is the bottleneck of human bandwidth—both in processing AI outputs and providing inputs. That's why I'm so excited to see Generative Interface by @StevenyzZhang and @CHEN_JIAQI_00 finally released! Check out the thread for more details⬇️
A key challenge in human-AI collaboration is the bottleneck of human bandwidth—both in processing AI outputs and providing inputs. That's why I'm so excited to see Generative Interface by @StevenyzZhang and @CHEN_JIAQI_00 finally released! Check out the thread for more details⬇️
(((ل()(ل() 'yoav)))... @yoavgo
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Delip Rao e/σ @deliprao
61K Followers 5K Following Busy inventing the shipwreck. @Penn. Past: @johnshopkins, @UCSC, @Amazon, @Twitter ||Art: #NLProc, Vision, Speech, #DeepLearning || Life: 道元, improv, running 🌈
Richard Socher @RichardSocher
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Percy Liang @percyliang
84K Followers 417 Following Associate Professor in computer science @Stanford @StanfordHAI @StanfordCRFM @StanfordAILab @stanfordnlp | cofounder @togethercompute | Pianist
Christopher Manning @chrmanning
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Tim Dettmers @Tim_Dettmers
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(((ل()(ل() 'yoav)))... @yoavgo
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250K Followers 1K Following Cofounded and lead @PyTorch at Meta. Also dabble in robotics at NYU. AI is delicious when it is accessible and open-source.
Delip Rao e/σ @deliprao
61K Followers 5K Following Busy inventing the shipwreck. @Penn. Past: @johnshopkins, @UCSC, @Amazon, @Twitter ||Art: #NLProc, Vision, Speech, #DeepLearning || Life: 道元, improv, running 🌈
Richard Socher @RichardSocher
112K Followers 1K Following CEO @youdotcom MP @aixventuresHQ Before: Stanford Adj Prof in AI/NLP, Chief Scientist at Salesforce, MetaMind
Percy Liang @percyliang
84K Followers 417 Following Associate Professor in computer science @Stanford @StanfordHAI @StanfordCRFM @StanfordAILab @stanfordnlp | cofounder @togethercompute | Pianist
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151K Followers 228 Following Director, @StanfordAILab. Assoc. Director, @StanfordHAI. Founder, @stanfordnlp. Prof. CS & Linguistics, @Stanford. IP @aixventureshq. 🇦🇺 Do #NLProc & #AI. 👋
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77K Followers 2K Following a combination of a mediocre scientist, a mediocre manager, a mediocre advisor & a mediocre physicist at @nyuniversity (@CILVRatNYU) & @PrescientDesign
NeurIPS Conference @NeurIPSConf
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40K Followers 708 Following Associate professor @LTIatCMU. Co-founder/chief scientist @allhands_ai. I mostly work on modeling language.
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50K Followers 3K Following AI alignment + LLMs at Anthropic. On leave from NYU. Views not employers'. No relation to @s8mb. I think you should join @givingwhatwecan.
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