4 papers
Qwen-AgentWorld: Language World Models for General Agents
Yuxin Zuo, Zikai Xiao, Li Sheng +30
A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning. In this work, we investigat…
Beyond Safe Data: Pretraining-Stage Alignment with Regular Safety Reflection
Jinhan Li, Kexian Tang, Yihan Xu +2
To achieve deeper safety alignment for large language models (LLMs), recent efforts have studied how to push safety interventions earlier into the pretraining stage, primarily by f…
Strategic Planning and Rationalizing on Trees Make LLMs Better Debaters
Danqing Wang, Zhuorui Ye, Xinran Zhao +2
Winning competitive debates requires sophisticated reasoning and argument skills. There are unique challenges in the competitive debate: (1) The time constraints force debaters to…
Cooperative Strategic Planning Enhances Reasoning Capabilities in Large Language Models
Danqing Wang, Zhuorui Ye, Fei Fang +1
Enhancing the reasoning capabilities of large language models (LLMs) is crucial for enabling them to tackle complex, multi-step problems. Multi-agent frameworks have shown great po…