5 papers
DeepPlanner: Scaling Planning Capability for Deep Research Agents via Advantage Shaping
Wei Fan, Wenlin Yao, Zheng Li +6
Large language models (LLMs) augmented with multi-step reasoning and action generation abilities have shown promise in leveraging external tools to tackle complex tasks that requir…
Next-Token Prediction Task Assumes Optimal Data Ordering for LLM Training in Proof Generation
Chenyang An, Shima Imani, Feng Yao +8
In the field of large language model (LLM)-based proof generation, despite extensive training on large datasets such as ArXiv, LLMs still exhibit only modest performance on proving…
Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective
Zhoujun Cheng, Shibo Hao, Tianyang Liu +21
Reinforcement learning (RL) has emerged as a promising approach to improve large language model (LLM) reasoning, yet most open efforts focus narrowly on math and code, limiting our…
Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care
Fengpei Yuan, Nehal Hasnaeen, Ran Zhang +5
This study explores a novel approach to advancing dementia care by integrating socially assistive robotics, reinforcement learning (RL), large language models (LLMs), and clinical…
Configurable Foundation Models: Building LLMs from a Modular Perspective
Chaojun Xiao, Zhengyan Zhang, Chenyang Song +20
Advancements in LLMs have recently unveiled challenges tied to computational efficiency and continual scalability due to their requirements of huge parameters, making the applicati…