Author

Shuaiqiang Wang

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Jul 2026

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

DocOps is introduced, a deterministically verifiable evaluation framework underpinned by a hierarchical taxonomy that deconstructs document operations inspired by real-world practices into atomic dimensions and escalating workflow complexities that exposes the capability boundaries of agents in maintaining global document consistency.

Jiazhen Jiang, Boxi Cao, Lingyong Yan et al. · arXiv.org · 1 citation

Preprint Aug 2026

DuMateBench: Evaluating Autonomous Agents in Complex Real-World Workflows

DuMateBench, a real-session benchmark reconstructed from anonymized and privacy-screened user sessions collected from a large-scale production agent platform, is introduced, showing that performance under environmental perturbations is jointly shaped by the capabilities of the LLM and the surrounding agent framework.

Zechun Niu, Yu-Kun Zhao, Jia-Xin Zhang et al. · 0 citations

#natural language process... Preprint Nov 2025

Learning a Single Token to Replace Long System Prompts in LLMs

A lightweight training framework that learns a single Behavior-Equivalent Token that substantially reduces inference cost and frees nearly the entire context window for user inputs and model outputs.

Jiancheng Dong, Pengyue Jia, Jingyu Peng et al. · 2 citations