14 citations · 33 across the 24 of their papers we have counts for
7 papers · 1 filter
PaceReasoner: Label-Free Learning to Answer Briefly from Long Reasoning
Changguo Jia, Zhiyou Xiao, Xinbei Ma +5
Extended chain-of-thought reasoning improves problem-solving performance but increases inference cost and latency, motivating more accurate answers with shorter reasoning. We intro…
UrbanGround: From Local Perception to Spatial Agency in a Real-Scale City
Tianjie Ju, Zheng Wu, Yueqing Sun +15
Multimodal large language models (MLLMs) can interpret a street view, but reliable urban action depends on whether such local evidence remains useful after the agent starts to move…
Communication Policy Evolution for Proactive LLM Agents
Xinbei Ma, Jiyang Qiu, Yao Yao +10
LLM agents have rapidly evolved into autonomous systems, yet a persistent information gap remains between users and agents: communication is costly, while users' identical preferen…
Retrospective Progress-Aware Self-Refinement for LLM Agent Training
Xinbei Ma, Congmin Zheng, Jiyang Qiu +11
Long-horizon LLM-based agents receive rich environmental observations during interaction, yet outcome rewards provide limited explicit supervision about how individual actions adva…
Plan-MCTS: Plan Exploration for Action Exploitation in Web Navigation
Weiming Zhang, Jihong Wang, Jiamu Zhou +9
Large Language Models (LLMs) have empowered autonomous agents to handle complex web navigation tasks. While recent studies integrate tree search to enhance long-horizon reasoning,…
Adaptive Milestone Reward for GUI Agents
Congmin Zheng, Xiaoyun Mo, Xinbei Ma +10
Reinforcement Learning (RL) has emerged as a mainstream paradigm for training Mobile GUI Agents, yet it struggles with the temporal credit assignment problem inherent in long-horiz…
Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning
Zheng Wu, Xingyu Lou, Xinbei Ma +5
Large Language Model (LLM)-based agents significantly extend the utility of LLMs by interacting with dynamic environments. However, enabling agents to continually learn new tasks w…