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Keyword: zero-shot generalization ×Clear all

1 claim from 1 paper

1. Computer Science › Multimodal Machine Learning Applications

   Visual Instruction Tuning

   Liu, Li, Wu and Lee · arXiv (Cornell University) · 2023

   The authors use language-only GPT-4 to generate image-and-text instruction data, then train LLaVA, a model linking a vision encoder to an LLM, and report chat ability and benchmark results.

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   1. UncheckedAfter fine-tuning on the Science QA benchmark, combining LLaVA with GPT-4 reaches 92.53% accuracy, which the authors call a new state of the art.“When fine-tuned on Science QA, the synergy of LLaVA and GPT-4 achieves a new state-of-the-art accuracy of 92.53%.”