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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…
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…
ZipRL: Adaptive Multi-Turn Context Compression with Hindsight Response Replay
Zhexin Hu, Li Wang, Xiaohan Wang +4
Adaptive context compression is vital for scaling Large Language Models (LLMs) to complex, multi-turn agent tasks. However, rule-based compression methods may discard task-critical…
LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations?
Xiaohan Wang, Mingze Yin, Yilin Zhao +2
Advanced Large Multimodal Models (LMMs) have demonstrated impressive performance in K-12 reasoning tasks, exhibiting great promise as intelligent tutors. Realizing this potential r…
AMR-SD: Asymmetric Meta-Reflective Self-Distillation for Token-Level Credit Assignment
Zhenlin Wei, Pu Jian, Yingzhuo Deng +6
The alignment of Large Language Models (LLMs) for complex reasoning heavily relies on Reinforcement Learning with Verifiable Rewards (RLVR). However, standard algorithms like GRPO…
AutoSearch: Adaptive Search Depth for Efficient Agentic RAG via Reinforcement Learning
Jingbo Sun, Wenyue Chong, Songjun Tu +7
Agentic retrieval-augmented generation (RAG) systems enable large language models (LLMs) to solve complex tasks through multi-step interaction with external retrieval tools. Howeve…