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[ARTICLE · art-137801] src=arxiv.org ↗ pub= topic=computer-vision verified=true sentiment=· neutral

ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains

The ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains drew 20 valid submissions from 8 teams, testing visual question answering over documents spanning eight domains including business reports, scientific papers, slides, posters, maps, comics, infographics, and engineering drawings. The strongest systems moved beyond single-pass prompting to structured evidence extraction, retrieval, verification, and orchestration across multiple components, with entries ranging from zero-shot vision-language models to OCR and parser-augmented pipelines, agentic retrieval systems, multi-agent ensembles, and fine-tuned multimodal models.

by read1 min views1 publishedSep 23, 2026

arXiv:2609.25055v1 Announce Type: new Abstract: In this report we present results of the ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains. This competition aimed to advance research in document understanding through the task of Visual Question Answering (VQA). Building upon previous DocVQA benchmarks, this competition introduces challenging reasoning questions over a diverse collection of documents spanning eight domains, including business reports, scientific papers, slides, posters, maps, comics, infographics, and engineering drawings. The competition concluded with 20 valid submissions from 8 teams spanning zero-shot VLMs, OCR and parser-augmented pipelines, agentic retrieval systems, multi-agent ensembles, and fine-tuned multimodal models. The results show that the strongest systems move beyond single-pass prompting and instead rely on structured evidence extraction, retrieval, verification, and orchestration across multiple components.

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