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Liu et al.: LLaVA visual instruction tuning

Contribution grade

Multimodal instruction learning · Human-designed research method or resource

Reference score150,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Used language-only teacher-generated visual instruction data and a vision-encoder/language-model connector to train an open multimodal instruction-following assistant.

Scientific scope

Used language-only teacher-generated visual instruction data and a vision-encoder/language-model connector to train an open multimodal instruction-following assistant. CLIP, language-model backbones and synthetic instruction tuning are inherited. Teacher supervision uses image captions/object information rather than proving GPT4 saw each image. Synthetic relative scores are not a general percentage of human intelligence or independent factual verification.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. CLIP, language-model backbones and synthetic instruction tuning are inherited. Teacher supervision uses image captions/object information rather than proving GPT4 saw each image. Synthetic relative scores are not a general percentage of human intelligence or independent factual verification.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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