65 skills found · Page 1 of 3
Opencode-DCP / Opencode Dynamic Context PruningDynamic context pruning plugin for OpenCode - intelligently manages conversation context to optimize token usage
ModelTC / LightCompress[EMNLP 2024 & AAAI 2026] A powerful toolkit for compressing large models including LLMs, VLMs, and video generative models.
ZLKong / Awesome Collection Token ReductionA collection of token reduction (token pruning, merging, clustering, etc.) techniques for ML/AI
xuyang-liu16 / Awesome Token Level Model Compression📚 Collection of token-level model compression resources.
mit-han-lab / Spatten[HPCA'21] SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
Theia-4869 / FasterVLMOfficial code for paper: [CLS] Attention is All You Need for Training-Free Visual Token Pruning: Make VLM Inference Faster.
OpenGVLab / DiffRate[ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging techniques, while incorporating a differentiable compression rate.
kssteven418 / LTP[KDD'22] Learned Token Pruning for Transformers
Theia-4869 / CDPruner[NeurIPS 2025] Official code for paper: Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs.
HVision-NKU / GlimpsePruneOfficial repository of the paper "A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models"
microsoft / MoonlitThis is a collection of our research on efficient AI, covering hardware-aware NAS and model compression.
Theia-4869 / VisPruner[ICCV 2025] Official code for paper: Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs
vbdi / Divprune[CVPR 2025] DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models
cokeshao / HoliTom[NeurIPS 2025] HoliTom: Holistic Token Merging for Fast Video Large Language Models
Visual-AI / PruneVid[ACL 2025] PruneVid: Visual Token Pruning for Efficient Video Large Language Models
orailix / PACT[CVPR 2025] PACT: Pruning and Clustering-Based Token Reduction for Faster Visual Language Models
LaVi-Lab / AIM[ICCV 2025] Official code for "AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning"
mlvlab / Vid TLDROfficial implementation of CVPR 2024 paper "vid-TLDR: Training Free Token merging for Light-weight Video Transformer".
Danielement321 / HiPruneImplementation for HiPrune, a training-free visual token pruning method for VLM acceleration.
double125 / MADTPMADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer
