pith:OGXGRTKC
InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition
InternLM-XComposer generates articles with automatically inserted context-appropriate images while achieving state-of-the-art results on vision-language benchmarks.
arxiv:2309.15112 v5 · 2023-09-26 · cs.CV
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Claims
Our model consistently achieves state-of-the-art results across various mainstream benchmarks for vision-language foundational models, including MME Benchmark, MMBench, MMBench-CN, Seed-Bench, CCBench, QBench and Tiny LVLM.
That the custom human-plus-GPT-4V evaluation procedure for text-image composition reliably measures quality and that the training data strategies produce genuine comprehension rather than benchmark overfitting.
InternLM-XComposer generates articles with seamlessly integrated images and achieves state-of-the-art results on vision-language benchmarks including MME, MMBench, and Seed-Bench.
References
Cited by
Receipt and verification
| First computed | 2026-05-17T23:38:13.920003Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519 (pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
71ae68cd42b6665f139e28a1479cd211e56ebd782f3efa8b38a36b487ce38b84
Aliases
· ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OGXGRTKCWZTF6E46FCQUPHGSCH \
| 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: 71ae68cd42b6665f139e28a1479cd211e56ebd782f3efa8b38a36b487ce38b84
Canonical record JSON
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