5 citations · 7 across the 9 of their papers we have counts for
6 papers · 1 filter
CoworkEnv: Synthesizing Training Environments for Long-Horizon Cowork Agents
Zhongwei Xie, Yiming Du, Jiaxin Bai +10
AI coworkers must coordinate tools, communicate across turns, and act on changing workspace state while respecting workflow constraints. Constructing training experience for these…
CASE: Cost-Aware Stopping for Efficient Long-Video Agents
Yiming Du, Chenghao Liu, Zhiyuan Liu +4
Long-video agents can actively gather question-relevant evidence, but they typically leave a central decision implicit: when has the agent seen enough to answer? We propose CASE, a…
Write, Execute, Refine: From Skill Follower to Skill Optimizer via Reinforcement Learning from Execution Feedback
Kang Peng, Zhiwei Zhang, Yichen Zhang +7
Expert-written natural language skills can improve tool-using agents, yet agent-authored skills perform 8--11 points worse than using no skill. While inference-time loops can repai…
Mitigating Context Interference for Reliable and Efficient Search Agents
Boyang Xue, Bin Wu, Shuofei Qiao +8
Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the contexts…
MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models
Xiyu Ren, Zhaowei Wang, Yiming Du +11
Memory is essential for large vision-language models (LVLMs) to handle long, multimodal interactions, with two method directions providing this capability: long-context LVLMs and m…
Can Retrieval Heads See Images? Multimodal Retrieval Heads in Long-Context Vision-Language Models
Aaron Branson Cigres Li, Zhaowei Wang, Yu Zhao +9
Large vision-language models increasingly rely on long-context modeling to reason over documents, hour-level videos, and long-horizon agent trajectories, requiring them to locate r…