🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

🚨 Introducing LAQuer, accepted to #ACL2025 (main conf)! LAQuer provides more granular attribution for LLM generations: users can just highlight any output fact (top), and get attribution for that input snippet (bottom). This reduces the amount of text the user has to read by 2

Big news! 🎉 I’m joining UNC-Chapel Hill as an Assistant Professor in Computer Science starting next year! Before that, I’ll be spending time OpenAI working on LLM privacy. UNC Computer Science UNC NLP

🎉Excited to share that I’ll be starting my CS PhD journey at UNC-Chapel Hill UNC Computer Science this fall! 🎓 I’ll be working with the renowned Mohit Bansal at UNC NLP — a dream comes true! ✨ Huge thanks to everyone who's helped me get here. Can't wait to begin this new life and research journey! 🧳🚀

Excited to share GenerationPrograms! 🚀 How do we get LLMs to cite their sources? GenerationPrograms is attributable by design, producing a program that executes text w/ a trace of how the text was generated! Gains of up to +39 Attribution F1 and eliminates uncited sentences,

🥳Excited to share that I’ll be joining UNC Computer Science as postdoc this fall. Looking forward to work with Mohit Bansal & amazing students at UNC AI. I'll continue working on retrieval, aligning knowledge modules with LLM's parametric knowledge, and expanding to various modalities.

🎉 Yay, welcome hyunji amy lee -- super excited to have you join us as a postdoc! 🤗 Welcome to our MURGe-Lab + UNC AI + UNC Computer Science family & the beautiful Research Triangle area -- looking forward to the many fun+impactful collaborations together 🔥

🥳Our work UTGen & UTDebug on teaching LLMs to generate effective unit tests & improve code debugging/generation has been accepted to Conference on Language Modeling #COLM2025! Stay tuned for more exciting results -- e.g., using 32B-scale UTGen models to improve debugging with frontier models like

🎉 Very excited to see TaCQ — our work on task-conditioned mixed-precision quantization that draws on interpretability methods — accepted to Conference on Language Modeling #COLM2025 with strong scores and a nice shoutout from the AC! Kudos to Hanqi on leading this effort!

🚨Introducing Video-RTS: Resource-Efficient RL for Video Reasoning with Adaptive Video TTS! While RL-based video reasoning with LLMs has advanced, the reliance on large-scale SFT with extensive video data and long CoT annotations remains a major bottleneck. Video-RTS tackles

🥳 Excited to share our work -- Retrieval-Augmented Generation with Conflicting Evidence -- on addressing conflict in RAG due to ambiguity, misinformation, and noisy/irrelevant evidence has been accepted to Conference on Language Modeling #COLM2025! Our new benchmark RAMDocs proves challenging for

🎉 Glad to see our work on handling conflicting & noisy evidence and ambiguous queries in RAG systems (via a new benchmark & multi-agent debate method) has been accepted to #COLM2025 Conference on Language Modeling!! 🇨🇦 Congrats to Han on leading this effort. More details in the thread below and

I’ll be at #ICML2025 this week to present ScPO: 📌 Wednesday, July 16th, 11:00 AM-1:30 PM 📍East Exhibition Hall A-B, E-2404 Stop by or reach out to chat about improving reasoning in LLMs, self-training, or just tips about being on the job market next cycle! 😃

🎉 Our paper, GenerationPrograms, which proposes a modular framework for attributable text generation, has been accepted to Conference on Language Modeling! GenerationPrograms produces a program that executes to text, providing an auditable trace of how the text was generated and major gains on

🥳 Gap year update: I'll be joining Ai2/University of Washington for 1 year (Sep2025-Jul2026 -> JHU Computer Science) & looking forward to working with amazing folks there, incl. Ranjay Krishna, Hanna Hajishirzi, Ali Farhadi. 🚨 I’ll also be recruiting PhD students for my group at JHU Computer Science for Fall

🚀 We introduce GrAInS, a gradient-based attribution method for inference-time steering (of both LLMs & VLMs). ✅ Works for both LLMs (+13.2% on TruthfulQA) & VLMs (+8.1% win rate on SPA-VL). ✅ Preserves core abilities (<1% drop on MMLU/MMMU). LLMs & VLMs often fail because

📢 Excited to share our new paper, where we introduce, ✨GrAInS✨, an inference-time steering approach for LLMs and VLMs via token attribution. Some highlights: ➡️GrAIns leverages contrastive, gradient-based attribution to identify the most influential textual or visual tokens

🚨 Excited to announce GrAInS, our new LLM/VLM steering method that uses gradient-based attribution to build more targeted interventions. Some highlights: 1️⃣ Compatible with both LLMs and VLMs, can intervene on text and vision tokens  2️⃣ Gains across variety of tasks +

🇦🇹 I’m on my way to #ACL2025 to help present two papers (🧵s below) ➡️ MAT-Steer (07/30 at 11am), our method for steering LLMs w/ multiple attributes (e.g. truthfulness, bias reduction, and toxicity mitigation) simultaneously. ➡️ LAQuer (07/28 at 11am), a new task/framework for

🚀 I'm recruiting PhD students to join my lab (jaehong31.github.io) at NTU Singapore (NTU Singapore), starting Spring 2026. If you're passionate about doing cutting-edge and high-impact research in multimodal AI, Trustworthy AI, continual learning, or video generation/reasoning,

Dear prospective PhD students: Check out Jaehong’s lab at NTU Singapore — one of the best places for cutting-edge research in multimodal, trustworthy, and continual learning AI!