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New benchmark reveals AI agents struggle with inferring document edits

By PulseAugur Editorial · [1 sources] ·

A new benchmark called WordInferBench has been introduced to evaluate the ability of AI agents to infer editing instructions from document context, rather than relying on fully specified commands. The benchmark, comprising 280 instances derived from real-world documents, tests agents on descriptive, referential, and inferential instruction conditions. Early evaluations using WordInferBench revealed that even the top-performing system, Claude Code with Opus 4.6, struggled with inferential tasks, achieving a significantly lower pass rate compared to descriptive instructions. AI

IMPACT This benchmark highlights a critical gap in current AI agent capabilities for real-world document editing tasks.

RANK_REASON The item is a research paper introducing a new benchmark for evaluating AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark reveals AI agents struggle with inferring document edits

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The item is a research paper introducing a new benchmark for evaluating AI agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jiayu Ding, Yupan Huang, Jinyoung Park, Yilin Jia, Wenshan Wu, Tengchao Lv, Shaohan Huang, Yuzhong Zhao, Xiangyang Zhou, Tao Ge, Sun Mao, Xun Wang, Huitian Jiao, Si-Qing Chen, Lei Cui, Nanning Zheng, Furu Wei ·

    WordInferBench: Can Agents Infer How to Edit from Word Document Context?

    arXiv:2611.15189v1 Announce Type: new Abstract: Document editing is among the most common knowledge-work tasks, yet existing benchmarks for evaluating autonomous agents on Word document editing provide fully specified attribute-modification instructions. They do not evaluate agen…

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