[QA] LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs

from Arxiv Papers · host Igor Melnyk

LLaVA-Scissor introduces a training-free token compression method for video multimodal models, utilizing Semantic Connected Components for effective, non-redundant semantic coverage, outperforming existing methods in various benchmarks. https://arxiv.org/abs//2506.21862 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

Episode metadata supplied by the publisher feed · Published Jun 30, 2025

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[QA] LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs

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