Archiki Prasad

@archiki.bsky.social

Ph.D. Student at UNC NLP | Apple Scholar in AI/ML Ph.D. Fellowship | Prev: FAIR at Meta, AI2, Adobe (Intern) | Interests: #NLP, #ML | https://archiki.github.io/

🌵 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

Elias Stengel-Eskin@esteng.bsky.social · 2y ago

🎉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

✈️ 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!

In Singapore for #ICLR2025 this week to present papers + keynotes 👇, and looking forward to seeing everyone -- happy to chat about research, or faculty+postdoc+phd positions, or simply hanging out (feel free to ping)! 🙂 Also meet our awesome students/postdocs/collaborators presenting their work.

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🚨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 🧵⬇️

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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). 🧵👇

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🎉 A big congratulations to @archiki.bsky.social (advised by Prof. @mohitbansal.bsky.social) for the being awarded the 2025 Apple Scholars in AI/ML PhD Fellowship!", we are proud of you! 👏

Archiki Prasad@archiki.bsky.social · last yr.

🥳🥳 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...

🎉🎉 Big congrats to @archiki.bsky.social on being awarded the @Apple AI/ML PhD Fellowship, for her extensive contributions in evaluating+improving reasoning in language/reward models and their applications to new domains (ReCEval, RepARe, System-1.x, ADaPT, ReGAL, ScPO, UTGen, GrIPS)! #ProudAdvisor

Archiki Prasad@archiki.bsky.social · last yr.

🥳🥳 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.

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🚨 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

Archiki Prasad@archiki.bsky.social · last yr.

🚨 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: 🧵👇

🚨 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: 🧵👇

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🎉 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 ... 🧵

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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 💙

UNC-Chapel Hill Computer Science@unccs.bsky.social · 2y ago

🎉 Congratulations to Prof. @mohitbansal.bsky.social for receiving the Presidential #PECASE Award by @WhiteHouse, which is the highest honor bestowed by US govt. on outstanding scientists/engineers who show exceptional potential for leadership early in their careers! whitehouse.gov/ostp/news-up...

Parker Distinguished Professor received the Presidential Early Career Award for Scientists and Engineers

✨ Collaborating with our amazing postdocs in our lab over the past year has been a great learning experience, with lots of fun + exciting research in LLM agents, reasoning, & multimodality! Check out the new postdoc openings and become a part of the vibrant research @unccs.bsky.social !⬇️

Mohit Bansal@mohitbansal.bsky.social · 2y ago

🚨 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 🙏

🚨 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 🙏

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I've truly enjoyed ✨ all of our collaborations ✨ over the past year. I particularly admire his thoughtful ideas, dedication to seeing them through, and his mentorship of junior students to do the same. I'm excited to see research from his lab as a professor and an advisor! 😄

Elias Stengel-Eskin@esteng.bsky.social · 2y ago

🚨 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" ➡️➡️ 🧵👇

Niranjan@niranjanb.bsky.social · 2y ago

Excited to host the wonderful @mohitbansal.bsky.social as part of Stony Brook CS Distinguished Lecture Series on Dec 6th. Looking forward to hearing about his team's fantastic work on Planning Agents for Collaborative Reasoning and Multimodal Generation. More here: tinyurl.com/jkmex3e9

A flyer announcing that Professor Mohit Bansal from the University of North Carolina Chapel Hill will present a Distinguished Lecture on Planning Agents for Collaborative Reasoning and Multimodal Generation at 2:30 PM in the New Computer Science Room 120 on Dec 6th 2024. The flyer also has a head shot of Mohit Bansal.

🚨 Reverse Thinking Makes LLMs Stronger Reasoners We can often reason from a problem to a solution and also in reverse to enhance our overall reasoning. RevThink shows that LLMs can also benefit from reverse thinking 👉 13.53% gains + sample efficiency + strong generalization (on 4 OOD datasets)!

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