NUS Proposes Parallel Autoregressive Decoding for Efficient Dense Video Captioning
NationalUniversityofSingapore · hf · 2026-07-08
The National University of Singapore proposed a parallel autoregressive decoding framework for Omni-Modal Dense Video Captioning. The research found that distant video events exhibit weak local dependencies, a characteristic that can be leveraged to parallelize the originally sequential autoregressive generation process. This drastically improves generation efficiency while maintaining temporal localization accuracy. This method offers a viable solution to the efficiency bottleneck of long-sequence generation in large-scale video understanding.
Related event: Parallel Autoregressive Decoding Framework Boosts Dense Video Captioning(2 posts)→
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