13 papers
CODA: Difficulty-Aware Compute Allocation for Adaptive Reasoning
Siye Wu, Jian Xie, Yikai Zhang +1
The emergence of large reasoning models demonstrates that scaling inference-time compute significantly enhances performance on complex tasks. However, it often falls into another t…
From AI Assistant to AI Scientist: Autonomous Discovery of LLM-RL Algorithms with LLM Agents
Sirui Xia, Yikai Zhang, Aili Chen +3
Discovering improved policy optimization algorithms for language models remains a costly manual process requiring repeated mechanism-level modification and validation. Unlike simpl…
The Lighthouse of Language: Enhancing LLM Agents via Critique-Guided Improvement
Ruihan Yang, Fanghua Ye, Jian Li +5
Large language models (LLMs) have recently transformed from text-based assistants to autonomous agents capable of planning, reasoning, and iteratively improving their actions. Whil…
Enhancing Language Agent Strategic Reasoning through Self-Play in Adversarial Games
Yikai Zhang, Ye Rong, Siyu Yuan +3
Existing language agents often encounter difficulties in dynamic adversarial games due to poor strategic reasoning. To mitigate this limitation, a promising approach is to allow ag…
ARM: Adaptive Reasoning Model
Siye Wu, Jian Xie, Yikai Zhang +4
While large reasoning models demonstrate strong performance on complex tasks, they lack the ability to adjust reasoning token usage based on task difficulty. This often leads to th…
DEEPER Insight into Your User: Directed Persona Refinement for Dynamic Persona Modeling
Aili Chen, Chengyu Du, Jiangjie Chen +6
To advance personalized applications such as recommendation systems and user behavior prediction, recent research increasingly adopts large language models (LLMs) for human -readab…