collaborators

33 papers

cs.LG2026

Toward Plasticity-Preserving KL Regularization for Capability Retention in LLM Reinforcement Learning

Li Wang, Xiaodong Lu, Xiaohan Wang +4

Reinforcement learning (RL) has become a central paradigm for large language model (LLM) post-training, but optimization toward new objectives can degrade capabilities already pres…

cs.CL2026

UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams

Siyu Xia, Chenheng Zhang, Yanting Wu +8

Memory is essential for LLM agents to accumulate task experience and reuse task-specific execution strategies. However, real-world deployment over boundary-agnostic and evolving ta…

cs.AI2026

TAPO: Tool-Aware Policy Optimization via Credit Transfer for Multimodal Search Agents

Chengqi Dong, Chuhuai Yue, Hang He +6

We identify and formally characterize credit misassignment as a systematic failure mode of GRPO in tool-augmented multimodal search agents: its uniform broadcast of trajectory-leve…

cs.CV2026

VistaHop: Benchmarking Long-Horizon Visual DeepSearch

Hang He, Chuhuai Yue, Chengqi Dong +6

Visual DeepSearch tasks require multimodal large language models (MLLMs) to resolve complex visual queries by repeatedly inspecting image regions, grounding reasoning in visual evi…

cs.CL2026

Are Full Rollouts Necessary for On-Policy Distillation?

Yaocheng Zhang, Jiajun Chai, Yuqian Fu +7

On-policy distillation (OPD) provides dense teacher feedback along student-generated rollouts rather than fixed teacher traces and has emerged as a promising post-training paradigm…

cs.AI2026

LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Services

Hang He, Chuhuai Yue, Chengqi Dong +12

Recent advances in large reasoning models LRMs have enabled agentic search systems to perform complex multi-step reasoning across multiple sources. However, most studies focus on g…