TinyLLaVA-Video-R1
Collection
Towards Smaller LMMs for Video Reasoning.
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4 items
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Updated
Here, we introduce a small-scale video reasoning model TinyLLaVA-Video-R1, based on the traceably trained model TinyLLaVA-Video. After reinforcement learning on general Video-QA datasets, the model not only significantly improves its reasoning and thinking abilities, but also exhibits the emergent characteristic of “aha moments”.
Result
| Model (HF Path) | Video-MME | MVBench | MLVU | MMVU |
|---|---|---|---|---|
| Zhang199/TinyLLaVA-Video-R1 | 46.6 | 49.5 | 52.4 | 46.9 |
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