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New benchmark evaluates PDF parsers for mathematical formula extraction

Researchers have developed a new framework for evaluating how well document parsers can extract mathematical formulas from PDFs. This system uses synthetically generated PDFs with precise LaTeX ground truth and employs an LLM-as-a-judge approach to assess the semantic equivalence of parsed formulas. Evaluating over 20 parsers on 100 synthetic documents revealed significant performance differences, offering guidance for practitioners. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Provides a standardized method to evaluate and improve AI's ability to process and understand mathematical content within academic literature.

RANK_REASON The cluster contains an academic paper detailing a new benchmarking framework for evaluating PDF parsers on mathematical formula extraction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

COVERAGE [1]

  1. arXiv cs.CV TIER_1 · Pius Horn, Janis Keuper ·

    Benchmarking Document Parsers on Mathematical Formula Extraction from PDFs

    arXiv:2512.09874v2 Announce Type: replace Abstract: Correctly parsing mathematical formulas from PDFs is critical for training large language models and building scientific knowledge bases from academic literature, yet existing benchmarks either exclude formulas entirely or lack …