most citedContextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards

1 citations · 1 across the 15 of their papers we have counts for

collaborators

29 papers

cs.CL2026

HiDiffTIR: Hierarchical Difficulty-Aware Policy Optimization for Multi-Turn Tool-Integrated Reasoning

Yucan Guo, Xiaohan Wang, Miao Su +8

Tool-Integrated Reasoning (TIR) is a fundamental capability for LLM agents to solve complex tasks by interacting with external tools iteratively. Reinforcement Learning (RL) has be…

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.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…