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An Empirical Study of VLM Pipelines for Long-Document QA
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
An empirical study on Vision-Language Model pipelines evaluates retrieval, static, and agentic approaches for long-document QA.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 25 September 2026
- Collected by OneBench
- 26 Sept 2026, 03:01 UK
- Original headline
- An Empirical Study of VLM Pipelines for Long-Document QA ↗
Stored source excerpt
arXiv:2609.29933v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly used for long-document processing, where the inputs combine text with charts, tables, figures, and complex…
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