Complex documents such as scientific papers contain rich information in tables, figures, and equations; however, existing deep research (DR) agents typically reduce papers to OCR-extracted text. We in
DR Pixel is an open-source multimodal agent that performs deep research directly on rendered document page images, improving retrieval and reasoning over scientific papers through counterfactual credit reweighting.
Complex documents such as scientific papers contain rich information in tables, figures, and equations; however, existing deep research (DR) agents typically reduce papers to OCR-extracted text. We instead ask whether vision-language models (VLMs) can enable page-native deep research: directly retrieving and reasoning over rendered document page images. We introduce DR Pixel, the first open-source end-to-end multimodal DR agent that uses rendered page images as its sole retrieval and reasoning unit, operating over a corpus of 1.06M pages. To evaluate this setting, we construct DRPixelBench, a benchmark on scientific papers requiring reasoning over text, figures, tables, and equations.…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
DR Pixel: Page-Native Deep Research with Vision-Language Models was first seen on Hugging Face · Daily papers on Nov 4, 2026. Since then it has appeared in 1 check on 1 different day. Its best position was #28 of 30, reached on Nov 4, 05:28 UTC. It dropped off the list after Nov 4, 05:28 UTC.
Position on Hugging Face · Daily papers at every check (lower is better).
Best rank per day (UTC).
Archived daily, weekly and monthly lists that include this entry.
Not at the moment. It was last on the list on Nov 4, 05:28 UTC, after 1 day of trending.
#28 on Hugging Face · Daily papers, on Nov 4, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 4, 2026 and has been on the list on 1 day (1 check) since.