docops-a-verifiable-benchmark-for-autonomous-agent

name	docops-a-verifiable-benchmark-for-autonomous-agent
description	Skill generated from arXiv paper 2607.19865: DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations
metadata	{"arxiv":{"id":"2607.19865","title":"DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations","authors":["Jiazhen Jiang","Boxi Cao","Lingyong Yan","Yaojie Lu","Hongyu Lin","Shuaiqiang Wang","Dawei Yin","Xianpei Han","Le Sun"],"published":"2026-07-22","categories":["cs.AI","cs.CL","cs.LG"],"url":"https://arxiv.org/abs/2607.19865","utility":1}}

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

arXiv: 2607.19865
Published: 2026-07-22
Authors: Jiazhen Jiang, Boxi Cao, Lingyong Yan, Yaojie Lu, Hongyu Lin, Shuaiqiang Wang, Dawei Yin, Xianpei Han, Le Sun
Categories: cs.AI, cs.CL, cs.LG
Utility: 1.00

Key Innovation

As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose AI assistants and automating complex workspace workflows. In this paper, we introduce DocOps, 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. Based on DocOps, we systematica...

Potential Application

This paper presents advancements that could be applied to enhance agent capabilities in the areas of cs.AI, cs.CL, cs.LG.

References

• arXiv: https://arxiv.org/abs/2607.19865