Shypd.aiThe largest open index of AI toolsAwesome-Token-Compress is a research paper list focused on token compression for Vision Transformer (ViT) and Vision-Language Models (VLM). It curates recent works on efficient VLM inference and video understanding.
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Awesome-Token-Compress is a comprehensive curated list of recent research papers dedicated to token compression techniques for Vision Transformer (ViT) and Vision-Language Models (VLM). This GitHub repository serves as a valuable resource for researchers and developers interested in optimizing the efficiency of large vision-language models. It features a wide array of works, including studies on approximation-error guided token compression, dual-stage efficient token reduction, and dynamic token compression for various applications like video understanding. The collection spans papers from 2024 to 2026, highlighting advancements in areas such as spatiotemporal token merging, attention-shift-aware pruning, and reinforcement learning-guided compression, making it an essential reference for staying updated on the latest developments in the field.
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