Some personal updates: - I've completed my PhD at @unccs.bsky.social! 🎓 - Starting Fall 2026, I'll be joining the CS dept. at Johns Hopkins University @jhucompsci.bsky.social as an Assistant Professor 💙 - Currently exploring options for my gap year (Aug 2025 - Jul 2026), so feel free to reach out! 🔎

📢 The SoLaR workshop will be collocated with COLM! @colmweb.org SoLaR is a collaborative forum for researchers working on responsible development, deployment and use of language models. We welcome both technical and sociotechnical submissions, deadline July 5th!

🚨 Introducing our @tmlrorg.bsky.social paper “Unlearning Sensitive Information in Multimodal LLMs: Benchmark and Attack-Defense Evaluation” We present UnLOK-VQA, a benchmark to evaluate unlearning in vision-and-language models, where both images and text may encode sensitive or private information.

🔥 BIG CONGRATS to Elias (and UT Austin)! Really proud of you -- it has been a complete pleasure to work with Elias and see him grow into a strong PI on *all* axes 🤗 Make sure to apply for your PhD with him -- he is an amazing advisor and person! 💙

Extremely excited to announce that I will be joining @utaustin.bsky.social Computer Science in August 2025 as an Assistant Professor! 🎉

🌵 I'm going to be presenting PBT at #NAACL2025 today at 2PM! Come by poster session 2 if you want to hear about: -- balancing positive and negative persuasion -- improving LLM teamwork/debate -- training models on simulated dialogues With @mohitbansal.bsky.social and @peterbhase.bsky.social

I will be presenting ✨Reverse Thinking Makes LLMs Stronger Reasoners✨at #NAACL2025! In this work, we show - Improvements across 12 datasets - Outperforms SFT with 10x more data - Strong generalization to OOD datasets 📅4/30 2:00-3:30 Hall 3 Let's chat about LLM reasoning and its future directions!

✈️ Heading to #NAACL2025 to present 3 main conf. papers, covering training LLMs to balance accepting and rejecting persuasion, multi-agent refinement for more faithful generation, and adaptively addressing varying knowledge conflict. Reach out if you want to chat!

Check out 🚨CAPTURe🚨 -- a new benchmark testing spatial reasoning by making VLMs count objects under occlusion. SOTA VLMs (GPT-4o, Qwen2-VL, Intern-VL2) have high error rates on CAPTURe (but humans have low error ✅) and models struggle to reason about occluded objects. arxiv.org/abs/2504.15485 🧵👇

🚨Real-world retrieval is messy: queries are ambiguous or docs conflict & have incorrect/irrelevant info. How can we jointly address these problems? ➡️RAMDocs: challenging dataset w/ ambiguity, misinformation & noise ➡️MADAM-RAG: multi-agent framework, debates & aggregates evidence across sources 🧵⬇️

Excited to share my first paper as first author: "Task-Circuit Quantization" 🎉 I led this work to explore how interpretability insights can drive smarter model compression. Big thank you to @esteng.bsky.social, Yi-Lin Sung, and @mohitbansal.bsky.social for mentorship and collaboration. More to come

What if we could transform advanced math problems into abstract programs that can generate endless, verifiable problem variants? Presenting EFAGen, which automatically transforms static advanced math problems into their corresponding executable functional abstractions (EFAs). 🧵👇

🚨Announcing TaCQ 🚨 a new mixed-precision quantization method that identifies critical weights to preserve. We integrate key ideas from circuit discovery, model editing, and input attribution to improve low-bit quant., w/ 96% 16-bit acc. at 3.1 avg bits (~6x compression) 📃 arxiv.org/abs/2504.07389

🥳🥳 Honored and grateful to be awarded the 2025 Apple Scholars in AI/ML PhD Fellowship! ✨ Huge shoutout to my advisor @mohitbansal.bsky.social, & many thanks to my lab mates @unccs.bsky.social , past collaborators + internship advisors for their support ☺️🙏 machinelearning.apple.com/updates/appl...

Introducing VEGGIE 🥦—a unified, end-to-end, and versatile instructional video generative model. VEGGIE supports 8 skills, from object addition/removal/changing, and stylization to concept grounding/reasoning. It exceeds SoTA and shows 0-shot multimodal instructional & in-context video editing.

🚨UPCORE is our new method for balancing unlearning/forgetting with maintaining model performance. Best part is it works by selecting a coreset from the data rather than changing the model, so it is compatible with any unlearning method, with consistent gains for 3 methods + 2 tasks!

🚨 Introducing UPCORE, to balance deleting info from LLMs with keeping their other capabilities intact. UPCORE selects a coreset of forget data, leading to a better trade-off across 2 datasets and 3 unlearning methods. 🧵👇

🚨 Check out "UTGen & UTDebug" for learning to automatically generate unit tests (i.e., discovering inputs which break your code) and then applying them to debug code with LLMs, with strong gains (>12% pass@1) across multiple models/datasets! (see details in 🧵👇) 1/4

🚨 Excited to announce UTGen and UTDebug, where we first learn to generate unit tests and then apply them to debugging generated code with LLMs, with strong gains (+12% pass@1) on LLM-based debugging across multiple models/datasets via inf.-time scaling and cross-validation+backtracking! 🧵👇

🚨 Excited to share: "Learning to Generate Unit Tests for Automated Debugging" 🚨 which introduces ✨UTGen and UTDebug✨ for teaching LLMs to generate unit tests (UTs) and debugging code from generated tests. UTGen+UTDebug yields large gains in debugging (+12% pass@1) & addresses 3 key questions: 🧵👇

🎉 Congrats to the awesome students, postdocs, & collaborators for this exciting batch of #ICLR2025 and #NAACL2025 accepted papers (FYI some are on the academic/industry job market and a great catch 🙂), on diverse, important topics such as: -- adaptive data generation environments/policies ... 🧵

🎉Very excited that our work on Persuasion-Balanced Training has been accepted to #NAACL2025! We introduce a multi-agent tree-based method for teaching models to balance: 1️⃣ Accepting persuasion when it helps 2️⃣ Resisting persuasion when it hurts (e.g. misinformation) arxiv.org/abs/2410.14596 🧵 1/4

🎉Congratulations to Prof. @mohitbansal.bsky.social on being named a 2025 @RealAAAI Fellow for "significant contributions to multimodal AI foundations & faithful language generation and summarization." 👏 16 Fellows chosen worldwide by cmte. of 9 past fellows & ex-president: aaai.org/about-aaai/a...

Congrats @mohitbansal.bsky.social for being selected to be part of this prestigious #AAAI Fellows group! Very well-deserved recognition of long-term contributions 🎉🎉

Congrats on this huge (and well-deserved) accomplishment @mohitbansal.bsky.social!

Deeply honored & humbled to have received the Presidential #PECASE Award by the @WhiteHouse and @POTUS office! 🙏 Most importantly, very grateful to my amazing mentors, students, postdocs, collaborators, and friends+family for making this possible, and for making the journey worthwhile + beautiful 💙

Apply soon to - work with tons of extremely talented and strong students and get hands-on experience mentoring - benefit from expert mentorship - be in a great department and live in an area with high quality of life and more! Feel free to ping me if you want to hear more from a current postdoc!

🚨 We have postdoc openings at UNC 🙂 Exciting+diverse NLP/CV/ML topics**, freedom to create research agenda, competitive funding, very strong students, mentorship for grant writing, collabs w/ many faculty+universities+companies, superb quality of life/weather. Please apply + help spread the word 🙏

✈️ I've landed in Vancouver for #NeurIPS2024 11/12: LACIE, a pragmatic speaker-listener method for training LLMs to express calibrated confidence: arxiv.org/abs/2405.21028 12/12: GTBench, a benchmark for game-theoretic abilities in LLMs: arxiv.org/abs/2402.12348 P.s. I'm on the faculty market👇

Working with Elias has been an absolute pleasure! His passion for research and dedication to mentoring are inspiring. Can’t wait to see all the amazing work his lab will do as he becomes a professor! ✨

Look out for @jmincho.bsky.social's application! He’s absolutely one of the top multimodal minds, I’ve been a fan of his work even before joining UNC and have been lucky enough to see him in action as a top-notch researcher and mentor!

🚨 I am on the faculty job market this year 🚨 I will be presenting at #NeurIPS2024 and am happy to chat in-person or digitally! I work on developing AI agents that can collaborate and communicate robustly with us and each other. More at: esteng.github.io and in thread below 🧵👇

Looking forward to giving this Distinguished Lecture at StonyBrook next week & meeting the several awesome NLP + CV folks there - thanks Niranjan‬ + all for the kind invitation 🙂 PS. Excited to give a new talk on "Planning Agents for Collaborative Reasoning and Multimodal Generation" ➡️➡️ 🧵👇

🚨Just read an exciting new paper from Justin 👇 on how to get the benefits of reasoning backwards (i.e. starting with the solution and tracing it back to the question) into a model while keeping the test-time cost of reasoning the same! 🧵1/3

Congratulations to #UNC CS student David Wan for winning the prestigious 2024 Google PhD Fellowship in NLP. 🎉🥳 A very well-deserved honor for his impactful work on factual and faithful text+multimodal generation with Prof. @mohitbansal.bsky.social and UNC NLP group! ▶️ blog.google/technology/r...

APPLY: TENURE-TRACK/TEACHING FACULTY. Research areas include but not limited to: ML, NLP, vision, graphics, systems, bioinformatics, security, medical imaging, robotics, RT systems, AR/VR. Join our team—committed to research, teaching, and collaboration. ➡️https://cs.unc.edu/faculty-hiring/

And it's a wrap at #EMNLP2024! Thanks everyone for joining us & making it memorable+engaging -- hope y'all enjoyed the program 🤗 💙 PS. A big thanks again to my co-chairs Thamar Solorio, Yun-Nung Chen, Yaser Al-Onaizan + the awesome committee members for all their effort! -- signing off, your PCs

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The thirdUnImplicit workshop on Understanding Implicit and Underspecified Language will be collocated with EACL 2024 in Malta! Co-organized with Alisa Liu, @esteng.bsky.social , Daniel Fried and Sandro Pezzelle. Submission deadline: 18th of Dec Website: unimplicit2024.github.io

I'm super excited for this workshop, and think that it's more relevant than ever. Models are now performing well at a lot of language tasks (sometimes even better than people). Does this mean language is solved? No -- it usually means our tasks are too easy. 1/4