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

arXiv cs.AI LLM Agents Jiazhen Jiang, Boxi Cao, Lingyong Yan, Yaojie Lu, Hongyu Lin, Shuaiqiang Wang, Dawei Yin, Xianpei Han, Le Sun 2026-07-22

TL;DR - DocOps is a deterministically verifiable benchmark for evaluating autonomous agents on increasingly complex document operations. It finds that frontier agent configurations still struggle with coupled, long-range workflows, highlighting barriers to reliable workspace automation.

  • Uses a hierarchical taxonomy to decompose realistic document operations into atomic capabilities and escalating workflow complexities.
  • Evaluates representative open- and closed-source models across multiple agentic harnesses.
  • Identifies three major failure modes: long-term state-tracking collapse, shallow semantic verification, and destructive editing of structural metadata.
  • Emphasizes global consistency and non-destructive editing as priorities for more robust document agents.

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