pith:RBKAZ7AD
ColPali: Efficient Document Retrieval with Vision Language Models
Directly embedding images of document pages with a vision language model outperforms text extraction pipelines in retrieval tasks.
arxiv:2407.01449 v6 · 2024-06-27 · cs.IR · cs.CL · cs.CV
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\pithnumber{RBKAZ7ADGTBMDY7K2SR4DB7UD5}
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Claims
ColPali largely outperforms modern document retrieval pipelines while being drastically simpler, faster and end-to-end trainable.
That direct image embeddings from a vision-language model capture all necessary semantic and layout information better than text extraction pipelines across the tested domains and languages.
ColPali embeds document page images with a vision-language model and late interaction to outperform text-based retrieval pipelines on a new visual document benchmark while being simpler and faster.
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| First computed | 2026-05-17T23:38:53.807452Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/RBKAZ7ADGTBMDY7K2SR4DB7UD5 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 88540cfc0334c2c1e3ead4a3c187f41f59f6489d63cba4485a298a737bd882eb
Canonical record JSON
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