activity
20242026
collaborators

61 papers

cs.AI2026

DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations

Jiazhen Jiang, Boxi Cao, Lingyong Yan +6

As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose AI assistants and automating…

cs.AI2026

DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent

Tongzhou Wu, Yuhao Wang, Xinyu Ma +4

Deep-research agents are capable of executing multi-step web exploration, targeted retrieval, and sophisticated question answering. Despite their powerful capabilities, deep-resear…

cs.AI2026

DuMate-DeepResearch: An Auditable Multi-Agent System with Recursive Search and Rubric-Grounded Reasoning

Lingyong Yan, Can Xu, Yukun Zhao +13

Deep Research (DR) has emerged as a new agentic paradigm to tackle complex, open-ended research tasks, demanding systems that can iteratively frame problems, acquire evidence, veri…

cs.AI2026

When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents

Dongsheng Zhu, Xuchen Ma, Yucheng Shen +5

Existing benchmarks evaluate Tool-Integrated Reasoning (TIR) in LLMs on idealized ''happy paths'', largely overlooking real-world tool failures. We introduce ToolMaze, a benchmark…

cs.CL2026

LLMs + Persona-Plug = Personalized LLMs

Jiongnan Liu, Yutao Zhu, Shuting Wang +6

Personalization plays a critical role in numerous language tasks and applications, since users with the same requirements may prefer diverse outputs based on their individual inter…

cs.CL2026

Measuring Maximum Activations in Open Large Language Models

Luxuan Chen, Han Tian, Xinran Chen +9

The dynamic range of activations is a first-order constraint for low-bit quantization, activation scaling, and stable LLM inference. Prior work characterized outlier features and m…