From the 2 of 12 linked papers with an AI index.
12 papers
Weak-to-Strong On-Policy Distillation
Fangxu Yu, Zinan Lin, Xiaodong Liu +4
The paper proposes Weak-to-Strong On-Policy Distillation (W2S-OPD), a method that improves a large language model by distilling knowledge from multiple weaker models using a constr…
GFlowRL: Scaling Distribution-Matching RL to Large Language Models
Xiaodong Liu, Michael Xu, Jack W. Stokes +3
The paper introduces GFlowRL, a simplified GFlowNet‑style reinforcement learning method that removes the learned partition function and uses an in‑batch Monte Carlo estimate, enabl…
PolyAlign: Conditional Human-Distribution Alignment
L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2
Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…
MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety
Jialin Song, Xiaodong Liu, Weiwei Yang +4
We present MultiBreak, a scalable and diverse multi-turn jailbreak benchmark to evaluate large language model (LLM) safety. Multi-turn jailbreaks mimic natural conversational setti…
Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents
Reuben Tan, Baolin Peng, Zhengyuan Yang +16
Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally optimized using sparse, outcome-bas…
Training Large Reasoning Models Efficiently via Progressive Thought Encoding
Zeliang Zhang, Xiaodong Liu, Hao Cheng +3
Large reasoning models (LRMs) excel on complex problems but face a critical barrier to efficiency: reinforcement learning (RL) training requires long rollouts for outcome-based rew…