Unified Spatio-Temporal Token Scoring for Efficient Video VLMs | ScienceToStartup | ScienceToStartup

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References (44)

[1]

Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding

2026Christopher Clark, Jieyu Zhang et al.

[2]

Qwen3-VL Technical Report

2025Shuai Bai, Yuxuan Cai et al.

[3]

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Founder's Pitch

"Introducing a novel token pruning technique for enhancing efficiency in vision-language models for video tasks."

Video VLM Optimization•Score: 3•View PDF ↗

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0-10 scale

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2.5

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2/4 signals

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1/4 signals

2.5

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Unified Spatio-Temporal Token Scoring for Efficient Video VLMs

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References (44)

Founder's Pitch

"Introducing a novel token pruning technique for enhancing efficiency in vision-language models for video tasks."

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Unified Spatio-Temporal Token Scoring for Efficient Video VLMs

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References (44)

Founder's Pitch

"Introducing a novel token pruning technique for enhancing efficiency in vision-language models for video tasks."

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