Alternatives and similar repositories for YOPO_MLLM_Pruning

Users that are interested in YOPO_MLLM_Pruning are comparing it to the libraries listed below

• shufangxun / LLaVA-MoD
  [ICLR 2025] LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation
  ☆210Updated 8 months ago
• alibaba / conv-llava
  ☆124Updated last year
• 42Shawn / LLaVA-PruMerge
  LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models
  ☆156Updated 2 months ago
• MME-Benchmarks / MME-RealWorld
  ✨✨ [ICLR 2025] MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
  ☆146Updated last month
• Theia-4869 / FasterVLM
  Official code for paper: [CLS] Attention is All You Need for Training-Free Visual Token Pruning: Make VLM Inference Faster.
  ☆97Updated 5 months ago
• SliMM-X / CoMP-MM
  Official repository of "CoMP: Continual Multimodal Pre-training for Vision Foundation Models"
  ☆35Updated 8 months ago
• ywh187 / FitPrune
  ☆61Updated 7 months ago
• Cooperx521 / PyramidDrop
  (CVPR 2025) PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction
  ☆134Updated 9 months ago
• ding523 / Curr_REFT
  ☆73Updated 6 months ago
• Kwai-YuanQi / MM-RLHF
  The Next Step Forward in Multimodal LLM Alignment
  ☆189Updated 7 months ago
• RUCAIBox / Virgo
  Official code of *Virgo: A Preliminary Exploration on Reproducing o1-like MLLM*
  ☆109Updated 6 months ago
• Fantasyele / LLaVA-KD
  [ICCV 2025] Official implementation of LLaVA-KD: A Framework of Distilling Multimodal Large Language Models
  ☆110Updated last month
• KangarooGroup / Kangaroo
  official impelmentation of Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input
  ☆67Updated last year
• RifleZhang / LLaVA-Reasoner-DPO
  ☆103Updated 10 months ago
• Adlith / MoE-Jetpack
  [NeurIPS 24] MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks
  ☆132Updated last year
• JinXins / Awesome-Token-Merge-for-MLLMs
  A paper list about Token Merge, Reduce, Resample, Drop for MLLMs.
  ☆75Updated last month
• HJYao00 / DenseConnector
  【NeurIPS 2024】Dense Connector for MLLMs
  ☆180Updated last year
• OpenGVLab / MM-NIAH
  [NeurIPS 2024] Needle In A Multimodal Haystack (MM-NIAH): A comprehensive benchmark designed to systematically evaluate the capability of…
  ☆117Updated last year
• hasanar1f / HiRED
  [AAAI 2025] HiRED strategically drops visual tokens in the image encoding stage to improve inference efficiency for High-Resolution Visio…
  ☆43Updated 7 months ago
• jefferyZhan / Griffon
  Official repo of Griffon series including v1(ECCV 2024), v2(ICCV 2025), G, and R, and also the RL tool Vision-R1.
  ☆245Updated 3 months ago
• OpenGVLab / LCL
  [NeurIPS 2024] Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
  ☆70Updated 9 months ago
• UCSC-VLAA / VLAA-Thinking
  [TMLR 25] SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
  ☆143Updated last month
• foundation-multimodal-models / CAPTURE
  ☆81Updated last year
• deepglint / UniME
  [ACM MM 2025] The official code of "Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs"
  ☆96Updated 3 weeks ago
• ZichenWen1 / DART
  [EMNLP 2025 main 🔥] Code for "Stop Looking for Important Tokens in Multimodal Language Models: Duplication Matters More"
  ☆91Updated last month
• BAAI-DCAI / DataOptim
  A collection of visual instruction tuning datasets.
  ☆76Updated last year
• x-cls / superclass
  [NeurIPS 2024] Classification Done Right for Vision-Language Pre-Training
  ☆219Updated 8 months ago
• MMStar-Benchmark / MMStar
  [NeurIPS 2024] This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"
  ☆200Updated last year
• Gumpest / SparseVLMs
  [ICML'25] Official implementation of paper "SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference".
  ☆200Updated 6 months ago
• foundation-multimodal-models / CAL
  [NeurIPS'24] Official PyTorch Implementation of Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
  ☆58Updated last year