Reroute turns irreversible visual-token pruning into recoverable routing that reuses existing attention scores, improving grounding performance under aggressive reduction on LLaVA-1.5 and Qwen while preserving TFLOPs and KV-cache budgets.
EvoPrune: Early-stage visual token pruning for efficient MLLMs
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Fre-Res compresses video tokens by preserving spatial anchors and representing temporal dynamics with low-frequency residual tokens derived from 1D-DCT on inter-frame residuals, plus a Spatial-Guided Absorber to reinject the information.
Training-free adaptive reuse of stable visual state in video VLMs reduces follow-up latency by 15-36x on Qwen2.5-VL while preserving correctness on VideoMME, with smaller first-query speedups via pruning.
citing papers explorer
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Reroute, Don't Remove: Recoverable Visual Token Routing for Vision-Language Models
Reroute turns irreversible visual-token pruning into recoverable routing that reuses existing attention scores, improving grounding performance under aggressive reduction on LLaVA-1.5 and Qwen while preserving TFLOPs and KV-cache budgets.
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Fre-Res: Frequency-Residual Video Token Compression for Efficient Video MLLMs
Fre-Res compresses video tokens by preserving spatial anchors and representing temporal dynamics with low-frequency residual tokens derived from 1D-DCT on inter-frame residuals, plus a Spatial-Guided Absorber to reinject the information.
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VLMaxxing through FrameMogging Training-Free Anti-Recomputation for Video Vision-Language Models
Training-free adaptive reuse of stable visual state in video VLMs reduces follow-up latency by 15-36x on Qwen2.5-VL while preserving correctness on VideoMME, with smaller first-query speedups via pruning.