UNC Computer Science

🚀 I'm recruiting PhD students to join my lab (jaehong31.github.io) at NTU Singapore (@NTUsg), 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,…

(1/7) I am delighted to share our paper, Classifying Unreliable Narrators with Large Language Models. If you are at #ACL2025, please come to our in-person oral presentation on Tuesday during Session 9 from 14:00-15:30 MESZ.

🇦🇹 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…

Will be attending #ACL2025. Happy to talk about the two papers being presented from our lab on (1) Identifying unreliable narrators w @AnnelieseB_ @shsriva (2) Improving fairness in multi-document summarization w @HaoyuanLi9 @ruizhang_nlp @uncnlp

🚨 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 +…

📢 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…

🚀 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…

Checkout our new paper: Video-RTS 🎥 A data-efficient RL method for complex video reasoning tasks. 🔹 Pure RL w/ output-based rewards. 🔹 Novel sparse-to-dense Test-Time Scaling (TTS) to expand input frames via self-consistency. 💥 96.4% less training data! More in the thread👇

🥳 Gap year update: I'll be joining @allen_ai/@UW for 1 year (Sep2025-Jul2026 -> @JHUCompSci) & looking forward to working with amazing folks there, incl. @RanjayKrishna, @HannaHajishirzi, Ali Farhadi. 🚨 I’ll also be recruiting PhD students for my group at @JHUCompSci for Fall…

As a @UNC student, Amy Xu ’25 used Carolina's makerspaces to build the escape room puzzles found in Chapel Thrill Escapes, a student-run business. Xu, who studied @unccs and @uncstor, said the challenge taught her how to solve problems without a manual go.unc.edu/d3H8N

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

The MUGen workshop at #ICML2025 is happening now! Stop by for talks on adversarial ML, unlearning as rational belief revision, failure modes in unlearning, robust LLM unlearning, and the bright vs. dark side of forgetting in generative AI!

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! 😃

Overdue job update -- I am now: - A Visiting Scientist at @schmidtsciences, supporting AI safety and interpretability - A Visiting Researcher at the Stanford NLP Group, working with @ChrisGPotts I am so grateful I get to keep working in this fascinating and essential area, and…

🎉 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 @COLM_conf!! 🇨🇦 Congrats to Han on leading this effort. More details in the thread below and…

🥳 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 @COLM_conf #COLM2025! Our new benchmark RAMDocs proves challenging for…

Video-RTS Rethinking Reinforcement Learning and Test-Time Scaling for Efficient and Enhanced Video Reasoning

🚨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…

I've officially joined Meta Superintelligence Labs (MSL) org in the Bay Area. I'll be working on critical aspects of pre-training, synthetic data and RL for the next generation of models. Humbled and eager to contribute to the quest for superintelligence. @AIatMeta

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