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New GDP.pdf benchmark reveals frontier models struggle with professional documents

A new benchmark called GDP.pdf has been released to evaluate multimodal reasoning capabilities on professional documents. The benchmark consists of 100 question-document pairs created by professionals, designed to challenge frontier multimodal models. When tested, the best performing model only achieved a 15% pass rate, indicating significant room for improvement in AI's ability to understand and reason over complex professional documents. AI

IMPACT Highlights limitations in current multimodal models for real-world professional document understanding, indicating a need for improved reasoning and grounding capabilities.

RANK_REASON The cluster describes a new academic benchmark for evaluating AI models on professional documents.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New GDP.pdf benchmark reveals frontier models struggle with professional documents

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Suhaas Garre, Emily Ritchie, Sushant Mehta, Edwin Chen ·

    GDP.pdf: Benchmarking Grounded Multimodal Reasoning over Professional PDF Documents

    arXiv:2607.11192v1 Announce Type: new Abstract: A large share of day-to-day work in professional domains happens inside PDF files: benefits packets, leases, datasheets, clinical guidelines, construction plans. Benchmarks for document AI have generally measured the required capabi…

  2. arXiv cs.CV TIER_1 English(EN) · Edwin Chen ·

    GDP.pdf: Benchmarking Grounded Multimodal Reasoning over Professional PDF Documents

    A large share of day-to-day work in professional domains happens inside PDF files: benefits packets, leases, datasheets, clinical guidelines, construction plans. Benchmarks for document AI have generally measured the required capabilities in isolation: OCR, layout analysis, chart…