17 papers
TsuGO: Probing Search Efficiency in LLM Reasoning via Go Life-and-Death Problems
Shunwen Bai, Ziping Ma, Chaoyang Zhang +4
The evaluation of LLM reasoning is moving from final-answer accuracy to process-level assessment, yet existing methods still fail to capture how models plan reasoning paths and all…
MemVLN: Episodic and Procedural Memory for Vision-and-Language Navigation
Yuqi Liu, Shengju Qian, Tianyuan Qu +5
Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to maintain long-horizon visual history for trajectory consistency while executing actions with l…
Orchestra-o1: Omnimodal Agent Orchestration
Fan Zhang, Vireo Zhang, Shengju Qian +8
The recent success of agent swarms has shifted the paradigm of large language model (LLM)-based agents from single-agent workflows to multi-agent systems, highlighting the importan…
OmniGameArena: A Unified UE5 Benchmark for VLM Game Agents with Improvement Dynamics
Mingxian Lin, Shengju Qian, Yuqi Liu +9
Vision-language model (VLM) agents are increasingly deployed in interactive game environments. Yet game benchmarks for VLM agents typically report a single first-attempt score per…
Policy and World Modeling Co-Training for Language Agents
Ning Lu, Baijiong Lin, Shengcai Liu +9
Reinforcement learning (RL) improves large language model (LLM) agents by teaching them which actions lead to high rewards, but provides little supervision on what those actions do…
On-Policy Adversarial Flow Distillation for Autoregressive Video Generation
Yang Luo, Shengju Qian, Xiaohang Tang +4
Autoregressive video generators are attractive for streaming, long-horizon, and interactive applications, but distilling strong black-box teachers into causal students remains diff…