Sharut Gupta @sharut_gupta
PhD student @MIT_CSAIL | @AIatMeta intern | ML Robustness, Generalization and self supervised learning | IIT Delhi’22 mit.edu/~sharut/ Boston, MA Joined August 2020-
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Our computer vision textbook is released! Foundations of Computer Vision with Antonio Torralba and Bill Freeman mitpress.mit.edu/9780262048972/… It’s been in the works for >10 years. Covers everything from linear filters and camera optics to diffusion models and radiance fields. 1/4
😎So excited to see that our In-context Attack (ICA) method has been leveraged by Anthrophic to break down the most prominent LLMs -- simply by extending # in-context examples! What a lesson of scaling!😆 See how this idea originates w/ @weizeming25 arxiv.org/abs/2310.06387
😎So excited to see that our In-context Attack (ICA) method has been leveraged by Anthrophic to break down the most prominent LLMs -- simply by extending # in-context examples! What a lesson of scaling!😆 See how this idea originates w/ @weizeming25 arxiv.org/abs/2310.06387
New paper :) "Dirichlet Flow Matching with Applications to DNA Sequence Design" arxiv.org/abs/2402.05841 TLDR 1. try linear flow matching on simplex 2. oh problem: explain 3. fix it with Dirichlet flow matching 4. Try on DNA, nice, better than language model 1/4
Models often fail under distribution shifts—can pre-training on a large and diverse dataset and then fine-tuning on a task-specific dataset help? W/ @bcohenwang, @josh_vendrow we show that this depends on the specific failure mode. In particular, pre-training can help with…
This is slightly late, but big thanks to @MITEECS for covering my work during my internship at @MITIBMLab this summer! Read about our work with VLMs here: eecs.mit.edu/reasoning-and-…
How do we better design classifiers that know when they don't know? There are two different kinds of uncertainty measures in the literature -- aleatoric, or due to inherent noise in the data from overlapping classes, and epistemic, or uncertainty due to atypical inputs.
Excited to share three new papers accepted by #ICLR2024 for understanding self-supervised learning: 1. (Spotlight) On the Role of Discrete Tokenization in Visual Representation Learning 2. Do Generated Data Always Help Contrastive Learning? 3. Non-negative Contrastive Learning 🧵
@iclr_conf Joint work with some awesome coauthors including @sharut_gupta, @dereklim_lzh, @SoledadVillar5, Yinan Huang, William Lu, @PanLi90769257, and of course... @StefanieJegelka!
Really excited to share that our recent work on mitigating confounders in multimodal molecular representation learning has been accepted at ICLR 2024! arxiv.org/abs/2312.00718
Really excited to share that our recent work on mitigating confounders in multimodal molecular representation learning has been accepted at ICLR 2024! arxiv.org/abs/2312.00718
🔉We just released EmphAssess, a benchmark for evaluating emphasis in speech to speech models. This work is a product of my internship at @metaai, and we’d gladly appreciate any feedback ! 📝 : arxiv.org/abs/2312.14069 👩💻 : github.com/facebookresear…
🌟 Excited to share our latest work "Event-Based Contrastive Learning for Medical Time Series" now available on Arxiv! 📄arxiv.org/pdf/2312.10308…. A big shout out to my amazing co-authors: Nassim, @MattBMcDermott @AparnaBee @payal_chandak @MarzyehGhassemi, and Collin! 🌟
How do we attribute an image generated by a diffusion model back to the training data? w/ @kris_georgiev1 @josh_vendrow @hadisalmanX @smsampark we show that it’s useful to look at each step of the diffusion process:
I’ll present InfoCORE “Removing Biases from Molecular Representations via Information Maximization” at 1:20pm in the AI4D3 workshop at #NeurIPS2023 today. Come and check our new molecular representation model at Room 242!
Last week I presented my @Apple internship project at the CALCS Workshop at #EMNLP23, and our work received the Best Paper Award! 🏆🥳 Big thanks to all my collaborators and especially to @matt_sperber. Check out the paper if you missed it! arxiv.org/abs/2310.12648
Unrelated to all the goings on at NeurIPS, this is now available on arXiv! Paper: arxiv.org/abs/2312.04615
Unrelated to all the goings on at NeurIPS, this is now available on arXiv! Paper: arxiv.org/abs/2312.04615
Super happy to share that our paper "LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers" was selected for an Outstanding Paper Award today at #EMNLP2023! 🎉🎉🎉
Thrilled to share our paper "Generating Novel Leads for Drug Discovery using LLMs with Logical Feedback" has been accepted at #AAAI2024 !!🎉 @TCSResearch @appcair biorxiv.org/content/10.110… (1/N)
Shaily @shaily99
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2K Followers 1K Following ML @MIT_CSAIL & @LiquidAI_ Symmetries in ML @bostonsymmetry Prev @NVIDIA @MetaAI @Cornell.Google DeepMind @GoogleDeepMind
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978K Followers 904 Following 🧑🍳. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets 🧠🤖💥François Chollet @fchollet
469K Followers 770 Following Deep learning @google. Creator of Keras. Author of 'Deep Learning with Python'. Opinions are my own.Kyunghyun Cho @kchonyc
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6K Followers 586 Following MIT Institute for Data, Systems, and Society focuses on complex, real-world problems requiring cross-disciplinary approaches. Part of @MIT_SCCWiDS-Cambridge @CambridgeWids
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1K Followers 503 Following Georgia Tech ML Researcher studying neural network learning theory and LLMs for mathematical reasoning. Intern at FAIR, MSFT Research. Co-founder of CarperAI.Ben Cohen-Wang @bcohenwang
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4K Followers 1K Following Alignment stress-testing team lead @AnthropicAI. Opinions my own. Previously: MIRI, OpenAI, Google, Yelp, Ripple. (he/him/his)Y Combinator @ycombinator
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1K Followers 127 Following PhD student at @StanfordNLP, @StanfordAILab. Ex: @GoogleDeepMind, @MSFTResearch Interested in structure and interpretation of human languagehazyresearch @HazyResearch
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576K Followers 0 Following Photos from the history of physics | © with mentioned Archives. Shared for educational purposes. Einstein portrait © Ullsteinbild. Subscribe for curated papers.rohan anil @_arohan_
12K Followers 2K Following Principal Engineer, @GoogleDeepMind Gemini. prev PaLM-2. Tinkering with optimization and distributed systems. opinions are my own.rishi @RishiBommasani
4K Followers 2K Following Stanford CS PhD @StanfordCRFM @StanfordNLP @StanfordAILab @StanfordHAI Advisers: @percyliang @jurafsky Previous: @CornellCIS @clairecardie #FoundationModelsIn academia, no one prepares you for starting a company. I recently had a private talk with UC Berkeley students. Honest and direct about starting a company in Techbio. Including the stuff no one says out loud. Full talk is now live: nfx.com/post/what-i-wi…
Going from researcher to founder is one of the most unintuitive transitions I have made. But it’s been an amazing journey. Here are my responses to the most common questions I hear from PhD students at @Mila_Quebec who want to start companies: 1/ How do I find a good idea to…
Excited to share Penzai, a JAX research toolkit from @GoogleDeepMind for building, editing, and visualizing neural networks! Penzai makes it easy to see model internals and lets you inject custom logic anywhere. Check it out on GitHub: github.com/google-deepmin…
Was a great honor to meet @NandanNilekani in DC. Nandan was the commencement speaker when I received my undergraduate degree at IIT Madras 6-7 years ago.
Are you a graduating / recently graduated Ph.D student (across the world) looking to do LLM research with a stellar group ⁉️ Join @partha_p_t as a Postdoc to advance multilingual LLMs!
Postdoc opening in Languages group at Google Deepmind based out of Bangalore Topics: LLMs, multilinguality, multimodality, RAI, etc. Strong candidates may apply by sending cv to [email protected] with [LLM-Postdoc] in subject by Apr 26 DM/email for any questions
Congrats to @AIatMeta on Llama 3 release!! 🎉 ai.meta.com/blog/meta-llam… Notes: Releasing 8B and 70B (both base and finetuned) models, strong-performing in their model class (but we'll see when the rankings come in @ @lmsysorg :)) 400B is still training, but already encroaching…
The super exciting TED talk on the SixthSense technology by @pranavmistry 14 years back inspired me a lot in many ways over the years 🔥. Finally got a chance to meet him and discuss research 😍. The TED talk video which I have watched a thousand times: youtube.com/watch?v=YrtANP……
Congrats to Dr Yatin Nandwani (my PhD #12), for completing his defense with flying colors. Yatin made many amazing contributions to neuro-symbolic ML, especially for tasks requiring both perception and reasoning. Joint with Prof Parag Singla)
Our computer vision textbook is released! Foundations of Computer Vision with Antonio Torralba and Bill Freeman mitpress.mit.edu/9780262048972/… It’s been in the works for >10 years. Covers everything from linear filters and camera optics to diffusion models and radiance fields. 1/4
Best student paper at #STOC2023 (1/2): Guy Blanc, surprisingly showing that subsampling suffices for adaptive data analysis! arxiv.org/abs/2302.08661
Excited to announce that [some other people] got two papers accepted at #NeurIPS2020! Guy Blanc, Neha Gupta, Jane Lange, and Li-Yang Tan have very interesting work on efficiently #learning decision trees. If you ever used stuff like C4.5, CART, or ID3, this may interest you. 1/2
Anyone else still does not feel how is our open-weights space is heating up rn? 🔥 The alignment team of @huggingface meets once a year... in Paris! 🇫🇷 And they have a few representatives of LLama 3🦙 alignment team over for a nice dinner! 🤗 @Meta @AIatMeta @MetaOpenSource
Google presents Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention 1B model that was fine-tuned on up to 5K sequence length passkey instances solves the 1M length problem arxiv.org/abs/2404.07143
Time machine: my friend @IritDinur and me & our partners Dana and Hadar, time of postdoc/phd @ Princeton. This is when we had enough complexity theory. Irit was about to invent differential privacy (w. Kobbi Nissim), and I was working on Online Convex Optimization (w.…
gist.github.com/ameya98/7f1035… for a barebones JAX implementation, allowing you to make any optax optimizer schedule-free! A version of this should be merged into optax soon :) github.com/google-deepmin…
Schedule-Free Learning github.com/facebookresear… We have now open sourced the algorithm behind my series of mysterious plots. Each plot was either Schedule-free SGD or Adam, no other tricks!
New Research: a lot of talk today about "what happens" inside a language model, since they spend the exact same amount of compute on each token, regardless of difficulty. we touch on this question on our new theory paper, Do Language Models Plan for Future Tokens?
Check out our #cvpr paper "Bridging Remote Sensors with Multisensor Geospatial Foundation Models" 🌍 . We introduce a multisensor geospatial foundation model that integrates four sensor modalities using cross sensor pretraining 🔍 Paper: lnkd.in/g3p-HDwc #foundationmodel