28 papers
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…
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…
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…
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…
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…
Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration
Zili Wang, Jiajun Chai, Lin Chen +3
Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as the standard paradigm for improving reasoning capability of large language models, while Multi-Token Prediction…