HyMOR combines MLLM for coarse open-ended recognition with CLIP for fine-grained domain objects, achieving near-CLIP fine performance and 2.5% better general recognition plus 23.2% overall SBert gain on a new TBO textbook dataset.
Why are visually-grounded language models bad at image classification? InThe Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
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Bridging Coarse and Fine Recognition: A Hybrid Approach for Open-Ended Multi-Granularity Object Recognition in Interactive Educational Games
HyMOR combines MLLM for coarse open-ended recognition with CLIP for fine-grained domain objects, achieving near-CLIP fine performance and 2.5% better general recognition plus 23.2% overall SBert gain on a new TBO textbook dataset.