Archit Sharma @archit_sharma97
Final-year CS PhD student @Stanford (on the job market!). Previously, AI Resident @Google Brain, undergraduate @IITKanpur, research intern @MILAMontreal. Joined July 2015-
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(1/N) Learning from preferences is a common paradigm for fine-tuning language models. Yet, many algorithmic design decisions come into play. Our new work finds that approaches employing on-policy sampling or negative gradients outperform offline, maximum likelihood objectives.
Can language models search in context? Turns out that explicitly training on search data and fine-tuning with *reinforcement learning* can substantially improve the ability of the model to search. Check out this work led by @gandhikanishk!
Can language models search in context? Turns out that explicitly training on search data and fine-tuning with *reinforcement learning* can substantially improve the ability of the model to search. Check out this work led by @gandhikanishk!
Introducing Yell At Your Robot (YAY Robot!) 🗣️- a fun collaboration b/w @Stanford and @UCBerkeley 🤖 We enable robots to improve on-the-fly from language corrections: robots rapidly adapt in real-time and continuously improve from human verbal feedback. YAY Robot enables…
After two years, it is my pleasure to introduce “DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset” DROID is the most diverse robotic interaction dataset ever released, including 385 hours of data collected across 564 diverse scenes in real-world households and offices
What if we want to change a LLM’s behavior using high-level verbal feedback like “can you use less comments when generating python code”? Check out our work on RLVF led by @at_code_wizard on how to fine-tune LLMs on such feedback without **overgeneralizing**!
What if we want to change a LLM’s behavior using high-level verbal feedback like “can you use less comments when generating python code”? Check out our work on RLVF led by @at_code_wizard on how to fine-tune LLMs on such feedback without **overgeneralizing**!
Some fascinating insights in this paper, and it really calls for us to reconsider how we conduct RLAIF We find that the current way of leveraging AI feedback is not as effective as doing SFT with strong teachers! Excited to see how this area of research will continue to progress
Some fascinating insights in this paper, and it really calls for us to reconsider how we conduct RLAIF We find that the current way of leveraging AI feedback is not as effective as doing SFT with strong teachers! Excited to see how this area of research will continue to progress
A Critical Evaluation of AI Feedback for Aligning Large Language Models Shows that the improvements of the RL step of LLM finetuning are virtually entirely due to the widespread practice of using a weaker teacher model (e.g. GPT-3.5) for SFT data collection than the critic…
Stanford presents RLVF Learning from Verbal Feedback without Overgeneralization The diversity of contexts in which large language models (LLMs) are deployed requires the ability to modify or customize default model behaviors to incorporate nuanced requirements and preferences.…
Jim Fan @DrJimFan
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Shreya Shankar @sh_reya
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Nathan Lambert @natolambert
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rohan anil @_arohan_
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Ted Xiao @xiao_ted
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Omar Sanseviero @osanseviero
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cultural archivist @cinder
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Michelle Li @michelleli__
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980 Followers 1K Following VP Product, https://t.co/M4BYZuOCI7, ex-AWS, Can watch any sport especially Test Cricket. Can play none well. Avid West Wing watcher. Maker of bad cocktails.
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121 Followers 1K Following #ArtificialIntelligence #MachineLearning #ComputerVision #3Dreconstruction #3Dmeasurement #ImageProcessing #Robotics #Programming #Packaging
Gabriel A. Melo @Gabruio
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Ronak Pradeep @rpradeep42
429 Followers 519 Following PhD at @UWaterloo. LLMs + IR. Research Internships @Apple @GoogleAI & @Mila_Quebec. There is no dark side in the moon, really. Matter of fact, it's all dark.
Adithyan @adithyan_ai
651 Followers 697 Following Amateur AI Enthusiast. Indie Hacker. Founder of : https://t.co/jTw4HMnjE2, https://t.co/iQDbtamv9b,
Zhi (Leo) Wang @TX_Leo_Wang
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Pensé FFun @inftyCategory
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Bbb @Bibb1234567
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Shreya Kapoor @SKapoor_18
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Yann LeCun @ylecun
710K Followers 718 Following Professor at NYU. Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate.
Andrej Karpathy @karpathy
978K Followers 904 Following 🧑🍳. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets 🧠🤖💥
AK @_akhaliq
310K Followers 3K Following AI research paper tweets, ML @Gradio (acq. by @HuggingFace 🤗) dm for promo follow on Hugging Face: https://t.co/q2Qoey80Gx
Jim Fan @DrJimFan
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Google DeepMind @GoogleDeepMind
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Sergey Levine @svlevine
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Karol Hausman @hausman_k
22K Followers 141 Following @Physical_int ex: researcher @GoogleAI/@DeepMind, adj. Prof. @Stanford. Into robots, AI, NBA, philosophy, soccer and almond croissants. 🇵🇱🇺🇸
François Chollet @fchollet
469K Followers 770 Following Deep learning @google. Creator of Keras. Author of 'Deep Learning with Python'. Opinions are my own.
Soumith Chintala @soumithchintala
186K Followers 877 Following Cofounded and lead @PyTorch at Meta. Also dabble in robotics at NYU. AI is delicious when it is accessible and open-source.
Animesh Garg @animesh_garg
21K Followers 1K Following Foundation Models for Generalizable Autonomy. Assistant Professor in AI Robotics @GeorgiaTech + @NvidiaAI. prev @Stanford @berkeley_ai @UofTCompSci
Peyman Milanfar @docmilanfar
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AI at Meta @AIatMeta
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Natasha Jaques @natashajaques
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Andrew Ng @AndrewYNg
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Physical Intelligence @physical_int
4K Followers 8 Following Physical Intelligence (Pi), bringing AI into the physical world.
Roshni Sahoo @roshni714
85 Followers 112 Following cs phd @Stanford | causal inference + ml | mit '20 | she/her
Eric Wallace @Eric_Wallace_
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Thomas Kollar @tkollar
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Jacob Collier @jacobcollier
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RFH🦎👁🗨�.. @hollowearthterf
38K Followers 986 Following Artemis Cultist. Loosh Harvester. Peattard. At eternal war with Rome. Infinite love is the only truth everything else is illusion!!!!!🇨🇳🏴🇮🇱🇦🇷
Kyla Scanlon @kylascan
168K Followers 918 Following wrote a book called "in this economy?" | (almost) daily economic videos | writing, podcast, and youtube 👻
Dwarkesh Patel @dwarkesh_sp
54K Followers 699 Following Being pretrained Host of Dwarkesh Podcast https://t.co/3SXlu7fy6N https://t.co/rEhnfYywXY https://t.co/hQfIWdM1Un
Michal Valko @misovalko
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Charlie Marx @CharlieTMarx
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Teortaxes▶️ @teortaxesTex
7K Followers 1K Following Ours is the age of unaligned utilitarians. Other problems are relatively unimportant, but sometimes I tweet about them anyway. (кто/кого)
Alex Graveley @alexgraveley
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Teknium (e/λ) @Teknium1
29K Followers 3K Following Cofounder @NousResearch, prev @StabilityAI Github: https://t.co/LZwHTUFwPq HuggingFace: https://t.co/sN2FFU8PVE Support me on Github Sponsors
Aviral Kumar @aviral_kumar2
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Jingyun Yang @yjy0625
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Karl Pertsch @KarlPertsch
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Elisa Kreiss @ElisaKreiss
983 Followers 999 Following Assistant Professor @UCLA. Linguistics PhD @stanfordnlp. Human-centered NLP | Cognitive Science | Accessibility. Lab director @CoalasLab. she/her.
Susan Zhang @suchenzang
20K Followers 503 Following @ Google Deepmind. Past: @MetaAI, @OpenAI, @unitygames, @losalamosnatlab, @Princeton etc. Always hungry for compute.
Priya Sundaresan @priyasun_
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Rylan Schaeffer @RylanSchaeffer
3K Followers 971 Following CS PhD student with @sanmikoyejo at @stai_research @StanfordAILab
Roma Patel @996roma
2K Followers 507 Following research scientist @deepmind london. language & rl & interpretability & safety. phd @BrownUniversity '22 with ellie pavlick. (she/her)
Aakanksha Chowdhery @achowdhery
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typedfemale @typedfemale
23K Followers 479 Following a really exciting new account "have you ever though you might be like scott alexander? very smart, but can't do math" - anon
Noam Brown @polynoamial
34K Followers 611 Following Researching reasoning @OpenAI | Co-created Libratus/Pluribus, the first superhuman no-limit poker AIs | Co-created CICERO | PhD from @SCSatCMU
Myle Ott @myleott
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John Schulman @johnschulman2
39K Followers 609 Following Cofounder @openai, lead post-training for ChatGPT and the API. Interested in reinforcement learning, alignment, birds, jazz music
rohan anil @_arohan_
12K Followers 2K Following Principal Engineer, @GoogleDeepMind Gemini. prev PaLM-2. Tinkering with optimization and distributed systems. opinions are my own.
Kawin Ethayarajh @ethayarajh
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Thomas Wolf @Thom_Wolf
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Dilip Arumugam @Dilip_Arumugam
436 Followers 622 Following CS PhD Candidate @StanfordAILab advised by Benjamin Van Roy | Reinforcement Learning & Information Theory | On the academic & industry job markets for 2023-2024
Rafael Rafailov @rm_rafailov
3K Followers 637 Following Ph.D. Student at @StanfordAILab. I work on Foundation Models and Decision Making. Previously @GoogleDeepMind @UCBerkeley
Xuechen Li @lxuechen
2K Followers 900 Following Building intelligence @xai. PhD @Stanford. Undergrad @UofT. Worked at @GoogleAI @MSFTResearch @Vectorinst. I go by Chen.
Sabera Talukder @SaberaTalukder
3K Followers 134 Following ✦Time Series Foundation Models @Caltech w/ @georgiagkioxari & @YisongYue 🦫 ✦SM Chair @CosyneMeeting 🧠 ✦Formerly @czbiohub @Stanford 🌲
David Krueger @DavidSKrueger
13K Followers 4K Following Cambridge faculty - AI alignment, deep learning, and existential safety. Formerly Mila, FHI, DeepMind, ElementAI, AISI.
The best part about making slides on LLM alignment is that I now get to combine my two passions in life: math and memes 😅 (this one is a classic from @tomgoldsteincs)
Most people rejected His message
the problem w/ the shoggoth mask metaphor is rlhf also increases capabilities. so it’s a shoggoth in a mask but it’s the mask (1994) w/ jim carrey
Thanks to @Anikait_Singh_ @archit_sharma97 @rm_rafailov Jeff @tengyangx @StefanoErmon @chelseabfinn and @aviral_kumar2 for being an amazing group of people to work with and learn from!
Overall, this was a fun collaboration & we learned a lot! Lots of experiments, analysis in the paper: understanding-rlhf.github.io/static/pdf/pap… (takeaway boxes if you don't have time) w/ @FahimTajwar10 @Anikait_Singh_ @archit_sharma97 @rm_rafailov Jeff @tengyangx @StefanoErmon @chelseabfinn
(1/N) Learning from preferences is a common paradigm for fine-tuning language models. Yet, many algorithmic design decisions come into play. Our new work finds that approaches employing on-policy sampling or negative gradients outperform offline, maximum likelihood objectives.
Excited to announce that I will be continuing my next chapter at @StanfordAILab for my Ph.D. in computer science!
L3 weights, *especially* Instruct, may be the most precious data pieces publicly available. They deserve being tended to – not slopped into a crude mockery of a closed frontier model by HF leaderboard champs. Continual pretraining, contextual sparsity, ReFT… Time to hit arxiv.
Introducing 𝐀𝐋𝐎𝐇𝐀 𝐔𝐧𝐥𝐞𝐚𝐬𝐡𝐞𝐝 🌋 - Pushing the boundaries of dexterity with low-cost robots and AI. @GoogleDeepMind Finally got to share some videos after a few months. Robots are fully autonomous filmed in one continuous shot. Enjoy!
A perfect weekend — had good food, met old friends, and finally, watched @BooleanAnalysis explain Croot-Sisask, and proof of Sander’s theorem :)
Grok is going multimodal! It’s incredible to see how fast a small, focused team can move. Kudos to the amazing team @xai that made this possible x.ai/blog/grok-1.5v
youtu.be/cPu3SecmgUU This phenomenon of young people having huge impact on the field is even more prominent in open source / open research IMO, because resource constraints force you to be more creative 😉 Some notable examples of LLM alignment research: - DPO, led by PhD…
The probability of a coin flip landing on heads 20 times in a row is infinitessimal, so if this doctor's last 20 patients have all survived a procedure with a 50% survival rate, that's an incredibly strong signal that this doctor is much better than average
PPO, DPO, IPO, CPO, KTO, and now BCO But what I really need right now is some PTO 😂
Why does Kahneman-Tversky Optimization (KTO) achieve successful alignment, even though it uses only binary signals? Check our Binary Classifier Optimization (BCO), which uncovers the connection between Direct Preference Optimization (DPO) and alignment from binary signal.
@SeungjaeJungML @ethayarajh @winniethexu @douwekiela @_lewtun @krasul @lvwerra @BanghuaZ @tomekkorbak @archit_sharma97 @rm_rafailov @Teknium1 Cool work, thanks for sharing! Related to what you were saying re: fixed bias in KTO a few months back @archit_sharma97
Why does Kahneman-Tversky Optimization (KTO) achieve successful alignment, even though it uses only binary signals? Check our Binary Classifier Optimization (BCO), which uncovers the connection between Direct Preference Optimization (DPO) and alignment from binary signal.
Introducing Udio, an app for music creation and sharing that allows you to generate amazing music in your favorite styles with intuitive and powerful text-prompting. 1/11
@archit_sharma97 @teortaxesTex @Teknium1 agreed =)
When I first saw Tree of Thoughts, I asked myself: If language models can reason better by searching, why don't they do it themselves during Chain of Thought? Some possible answers (and a new paper): 🧵
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