6 papers
TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training
Yuhang Zhou, Kai Zheng, Haoling Li +3
On-policy distillation (OPD) trains a student policy by matching a stronger teacher on the student's own trajectories, offering a promising framework for language agent training. H…
OffSeeker: Online Reinforcement Learning Is Not All You Need for Deep Research Agents
Yuhang Zhou, Kai Zheng, Qiguang Chen +4
Deep research agents have shown remarkable potential in handling long-horizon tasks. However, state-of-the-art performance typically relies on online reinforcement learning (RL), w…
AI4Research: A Survey of Artificial Intelligence for Scientific Research
Qiguang Chen, Mingda Yang, Libo Qin +13
Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs) such as OpenAI-o1 and DeepSeek-R1, have demonstrated remarkable capabilities in co…
Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models
Qiguang Chen, Libo Qin, Jinhao Liu +7
Recent advancements in reasoning with large language models (RLLMs), such as OpenAI-O1 and DeepSeek-R1, have demonstrated their impressive capabilities in complex domains like math…
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization
Jiaqi Wang, Yuhang Zhou, Zhixiong Zhang +3
Out-of-distribution generalization is a common problem that expects the model to perform well in the different distributions even far from the train data. A popular approach to add…
DLPO: Towards a Robust, Efficient, and Generalizable Prompt Optimization Framework from a Deep-Learning Perspective
Dengyun Peng, Yuhang Zhou, Qiguang Chen +3
Large Language Models (LLMs) have achieved remarkable success across diverse tasks, largely driven by well-designed prompts. However, crafting and selecting such prompts often requ…