Regarding the visual instruction tuning paper, see (https://arxiv.org/pdf/2402.11349.pdf, Table 5). Though this experiment on multi-modality was rather simple, I think it does show that it’s not a convenient way to improve on H-Test.
Yeah; I do wonder just how qualitatively different GPT4 or Gemini’s multimodality is from the ‘glue a vision classifier on then train it’ method LLaVa uses, since I don’t think we have specifics. Suspect it trained on image data from the start or near it rather than gluing two different transformers together, but hard to be sure.
Regarding the visual instruction tuning paper, see (https://arxiv.org/pdf/2402.11349.pdf, Table 5). Though this experiment on multi-modality was rather simple, I think it does show that it’s not a convenient way to improve on H-Test.
Yeah; I do wonder just how qualitatively different GPT4 or Gemini’s multimodality is from the ‘glue a vision classifier on then train it’ method LLaVa uses, since I don’t think we have specifics. Suspect it trained on image data from the start or near it rather than gluing two different transformers together, but hard to be sure.