arXiv:2607.01245v1 Announce Type: new Abstract: We introduce Office Comprehension Bench (OCB), the first public benchmark to jointly evaluate LLM systems on Word, Excel, and PowerPoint comprehension over native file formats (.docx, .xlsx, .pptx) and their variants. OCB consists of two tracks. File Fidelity Q&A tests structural and visual perception of office artifacts - tables, charts, embedded images, formulas, and app-specific elements such as headers, speaker notes, and named ranges. Domain Q&A tests expert-level reasoning grounded in real-world industry documents across 12 professional dom
The proliferation of advanced LLMs has necessitated more granular and realistic benchmarks to evaluate their practical application in enterprise settings, moving beyond idealized data.
This benchmark is crucial for assessing the true capabilities and limitations of AI agents interacting with ubiquitous enterprise software, directly impacting their deployability for automating knowledge work.
The introduction of OCB provides a standardized, real-world testing ground for LLMs in office environments, potentially accelerating the development and adoption of robust AI agents for business automation.
- · AI Agent Developers
- · Enterprise Software Vendors (integrating AI)
- · Consulting Firms (AI implementation)
- · Businesses adopting AI agents
- · Tasks requiring manual office software interaction
- · Inefficient software testing methodologies
Companies will gain clearer insights into which LLMs are genuinely capable of complex office tasks, leading to more informed AI procurement.
The benchmark could drive significant improvements in LLM architecture and fine-tuning specifically tailored for enterprise productivity applications.
Widespread adoption of highly capable office AI agents could dramatically reshape job roles and workflows within white-collar sectors, leading to efficiency gains but also workforce disruption.
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Read at arXiv cs.CL