mlsanityData to 14 Oct 2026

Evidence First, Arithmetic Second: A System Report and Failure Analysis for DocSem

arXiv 2609.39013 ↗First posted 30 Sep 2026cs.CL cs.IRcited by 0

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Abstract (arXiv)

EVICALC, our system for the DocSem shared task, achieved 8.61% joint accuracy on 1,730 tasks in the official final test evaluation. It reads a PDF, selects a passage, asks a language model to write an arithmetic expression, and evaluates that expression in local code. Saved intermediate results support inspection of failures. A separate public-validation run achieved 92.17% answer accuracy and 1.00 evidence F1. The configurations and metrics differ, so these scores are not a controlled comparison. Our manual, post-hoc analysis is descriptive: in one inspected case, optical character recognition (OCR) and block grouping merged the relevant passage into another block, and the system answered from unrelated text. An exploratory study of reading page images on 100 documents returned evidence identifiers for only 22 documents. These descriptive findings motivate further evaluation; they do not establish the causes of the overall score.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 7 references that are in the map. First posted on arXiv 30 Sep 2026.

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References · 2

  1. 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,317
  2. 2026GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentationscited by 2

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