Author

Gwang Lee

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#artificial intelligence Preprint Sep 2026

An Empirical Study of VLM Pipelines for Long-Document QA

Three of the strongest pipelines succeed on different questions, and an oracle that picks the best pipeline per question gains roughly thirteen points over the best single pipeline, though evidence-type routing recovers almost none of it.

K. E. Ak, Jay Mohta, Gwang Lee et al. · 0 citations

#artificial intelligence May 2026

Do VLMs Read or Rewrite? On Transcription Faithfulness in Vision-Language Models

It is shown VLMs do not always act as faithful transcribers: when text is imperfect, they often tend to rewrite it into a more plausible form - a behavior that clean-text OCR benchmarks cannot detect.

Gwang Lee, K. E. Ak, Jay Mohta et al. · arXiv.org · 2 citations · ⚡1