4 papers · 1 filter
Absolute Zero: Reinforced Self-play Reasoning with Zero Data
Andrew Zhao, Yiran Wu, Yang Yue +7
Reinforcement learning with verifiable rewards (RLVR) has shown promise in enhancing the reasoning capabilities of large language models by learning directly from outcome-based rew…
DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints
Andrew Zhao, Quentin Xu, Matthieu Lin +4
Recent advances in large language model assistants have made them indispensable, raising significant concerns over managing their safety. Automated red teaming offers a promising a…
ExpeL: LLM Agents Are Experiential Learners
Andrew Zhao, Daniel Huang, Quentin Xu +3
The recent surge in research interest in applying large language models (LLMs) to decision-making tasks has flourished by leveraging the extensive world knowledge embedded in LLMs.…
Exploring Text-to-Motion Generation with Human Preference
Jenny Sheng, Matthieu Lin, Andrew Zhao +5
This paper presents an exploration of preference learning in text-to-motion generation. We find that current improvements in text-to-motion generation still rely on datasets requir…