collaborators

11 papers

cs.AI2026

FACET: Preserving Source Intent and Executable State in Terminal Task Synthesis

Kou Shi, Zun Wang, Qisheng Su +10

Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples an instruction, an initialize…

cs.CV2026

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

Zhen Fang, Yu Zeng, Wenxuan Huang +17

We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense spatiotemporal grounding couple…

cs.CL2026

ACC: Compiling Agent Trajectories for Long-Context Training

Qisheng Su, Zhen Fang, Shiting Huang +8

Recent development of agents has renewed demand for long-context reasoning capacity of LLMs. However, training LLMs for this capacity requires costly long-document curation or heur…

cs.AI2026

SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents

Ziao Zhang, Kou Shi, Shiting Huang +13

As the capability frontier of autonomous agents continues to expand, they are increasingly able to complete specialized tasks through plug-and-play external skills. Yet current ben…

cs.PF2026

Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated Reasoning

Qisheng Su, Shiting Huang, Zhen Fang +3

In real-world Tool-Integrated Reasoning (TIR) scenarios, where LLMs interleave reasoning with external tool calls, a major source of inefficiency is that the toolcalls create pause…

cs.CV2026

Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models

Yu Zeng, Wenxuan Huang, Zhen Fang +14

Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, eva…