Pruning

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Pruning

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Visual Tokens

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Visual Token Pruning

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101 papersExplore

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Heterogeneous Pruning Scores

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363 papers

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Channel-wise Vector Quantization
May 25, 2026Wei Song, Tianhang Wang, Yitong Chen +5Autoregressive Image Generation Visual Tokens
VEN-VL: A Visual Ensemble MoE Framework for Effective and Efficient Multi-Modal Understanding
May 25, 2026Yinghao Wu, Zhuoyan Luo, Yiyao Yu +3Universal Multimodal Visual Tokens
MuCRASP: Multimodal Chain-of-thought Reasoning aware Structured Pruning
May 25, 2026Aritra Dutta, Somak AdityaMulti-Modal Large Language Models Visual Token Pruning
Grow-Prune-Freeze Networks: Adaptive & Continual Learning Technique for Olfactory Navigation
May 24, 2026Kordel K. France, Ovidiu DaescuEfficient Continual Learning Continual Learning Methods
Uncertainty-DTW for Sequences and Visual Tokens
May 24, 2026Lei Wang, Syuan-Hao Li, Yongsheng Gao +1Feature Matching Visual Tokens
Vision Transformers Need Better Token Interaction
May 22, 2026Linxiang SuVision Transformer Dense Prediction
CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs
May 22, 2026Xiaoyi Huang, Kejia Zhang, Zhiming LuoLarge Vision Language Models Contrastive Decoding
Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling
May 22, 2026Yeseul Cho, Baekrok Shin, Changmin Kang +1Pseudo-Labeling Heterogeneous Pruning Scores
Scout-Assisted Planning for Heterogeneous Robot Teams under Partially Known Environments
May 21, 2026Hoang-Dung Bui, Abhish Khanal, Raihan Islam Arnob +1Multi-Robot Systems Planning Methods
GeoWeaver: Grounding Visual Tokens with Geometric Evidence before Scene Reasoning
May 21, 2026Deshui Miao, Xingsen Huang, Yameng Gu +3Spatial Reasoning Geometry-Aware
ASAP: Attention Sink Anchored Pruning
May 21, 2026Jaehyuk Lee, Hanyoung Kim, Yanggee Kim +1Visual Token Pruning Vision Transformer
Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
May 21, 2026Fabian Morelli, Stephan EcksteinNeural Network Ensemble
ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs
May 21, 2026Bingjun Luo, Tony Wang, Chaoqi Chen +1Video Understanding Visual Tokens
Enhancing Visual Token Representations for Video Large Language Models via Training-Free Spatial-Temporal Pooling and Gridding
May 21, 2026Bingjun Luo, Tony Wang, Hanqi Chen +1Visual Tokens
Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning
May 19, 2026Zichao Zeng, June Moh Goo, Junwei Zheng +4Visual Place Recognition Visual Token Pruning
Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding
May 19, 2026Yuhao Shen, Tianyu Liu, Xinyi Hu +9Speculative Decoding Heterogeneous Pruning Scores
UniRefiner: Teaching Pre-trained ViTs to Self-Dispose Dross via Contrastive Register
May 19, 2026Congpei Qiu, Zhaoyu Hu, Wei Ke +3Self-Supervised Vision Transformers Vision Transformer
EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning
May 19, 2026Pengtao Ma, Ziliang Zhou, Ciyu Ruan +7Visual Token Pruning Spatial Attention
AQuaUI: Visual Token Reduction for GUI Agents with Adaptive Quadtrees
May 19, 2026Yuankai Li, Tinghui Zhu, Ha Min Son +3Graphical User Interface Agents Visual Tokens
Rotation-Aligned Key Channel Pruning for Efficient Vision-Language Model Inference
May 19, 2026Beomseok Kang, Dongwon Jo, Jiwon Song +2Visual Token Pruning Quadratic Attention
Vision Foundation Models as Generalist Tokenizers for Image Generation
May 18, 2026Anlin Zheng, Qi Han, Xin Wen +5Visual Tokens Image Generation
Prune, Update and Trim: Robust Structured Pruning for Large Language Models
May 18, 2026Diego Coello de Portugal Mecke, Tom Hanika, Lars Schmidt-ThiemeHeterogeneous Pruning Scores Pruning
WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens
May 18, 2026Yiwei Guo, Shaobin Zhuang, Zhipeng Huang +4Visual Tokens Tokenization
OmniSelect: Dynamic Modality-Aware Token Compression for Efficient Omni-modal Large Language Models
May 18, 2026Morunliu Yang, Ruotao Xu, Le Li +6Visual Token Pruning Omni-Modal
A More Word-like Image Tokenization for MLLMs
May 18, 2026Hyun Lee, Hyemin Jeong, Yejin Kim +4Visual Tokens Multi-Modal Large Language Models
Temporal Aware Pruning for Efficient Diffusion-based Video Generation
May 18, 2026Sheng Li, Yang Sui, Junhao Ran +3Spatio-Temporal Coherence Pruning
FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing
May 17, 2026Zihan Tang, Leqi Shen, Hui Chen +7Deepseek-Ocr Optical Character Recognition
Registers Matter for Pixel-Space Diffusion Transformers
May 15, 2026Nikita Starodubcev, Ilia Sudakov, Ilya Drobyshevskiy +2Multimodal Diffusion Transformers Self-Supervised Vision Transformers
Going Beyond the Edge: Distributed Inference of Transformer Models on Ultra-Low-Power Wireless Devices
May 15, 2026Alexander Gräfe, Ding Huo, Vincent de Bakker +3Resource-Constrained Edge Devices Parallel
LRCP: Low-Rank Compressibility Guided Visual Token Pruning for Efficient LVLMs
May 15, 2026Hongyu Lu, Feng Zhang, Wenwei Jin +5Visual Tokens Large Vision Language Models
On the Stability of Growth in Structural Plasticity
May 14, 2026Lute Lillo, Nick CheneyPlasticity Growth
Representative Attention For Vision Transformers
May 14, 2026Yuntong Li, Hainuo Wang, Hengxing Liu +2Self-Supervised Vision Transformers Vision Transformer
Hierarchical Image Tokenization for Multi-Scale Image Super Resolution
May 14, 2026Isma Hadji, Enrique Sanchez, Adrian Bulat +2Self-Supervised Vision Transformers Visual Autoregressive Models
OmniDrop: Layer-wise Token Pruning for Omni-modal LLMs via Query-Guidance
May 14, 2026Yeo Jeong Park, Hyemi Jang, Minseo Choi +3Visual Token Pruning Token Compression
InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation
May 14, 2026Yang Yue, Fangyun Wei, Tianyu He +10Autoregressive Image Generation Visual Tokens
CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers
May 13, 2026Zhuojin Li, Hsin-Pai Cheng, Hong Cai +2Multimodal Diffusion Transformers Visual Token Pruning
MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
May 13, 2026Cenwei Zhang, Suncheng Xiang, Lei YouPruning Boundaries
PreFIQs: Face Image Quality Is What Survives Pruning
May 13, 2026Jan Niklas Kolf, Guray Ozgur, Andrea Atzori +4Facial Recognition Face Embeddings
GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models
May 13, 2026Mingzhe Huang, Weijun Wang, Xin Ding +7Visual Token Pruning Large Vision Language Models
CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large VIsion-Language Models
May 13, 2026Sangin Lee, Yukyung ChoiVisual Token Pruning Visual Tokens
Learning to See What You Need: Gaze Attention for Multimodal Large Language Models
May 13, 2026Junha Song, Byeongho Heo, Geonmo Gu +3Visual Tokens Video Understanding
SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning
May 13, 2026Run Zou, Jianhang Ding, Yifan Ding +3Multimodal Instruction Tuning Training Data
VIP-COP: Context Optimization for Tabular Foundation Models
May 13, 2026Yilong Chen, Xueying Ding, Leman AkogluTabular Foundation Models In-Context Learning
Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs
May 12, 2026Jingzhou Jiang, Yi Yang, Kar Yan TamHeterogeneous Pruning Scores Model Selection
G $^2$ TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models
May 12, 2026Junxian Li, Kai Liu, Zizhong Ding +4Visual Tokens Unified Multimodal Models
See What Matters: Differentiable Grid Sample Pruning for Generalizable Vision-Language-Action Model
May 12, 2026Yixu Feng, Zinan Zhao, Yanxiang Ma +4Vision-Language-Action Models Visual Token Pruning
Keep What Audio Cannot Say: Context-Preserving Token Pruning for Omni-LLMs
May 12, 2026Chaeyoung Jung, Kyeongha Rho, Joon Son ChungVisual Token Pruning Audio-Visual Reasoning
Constraint-Data-Value-Maximization: Utilizing Data Attribution for Effective Data Pruning in Low-Data Environments
May 11, 2026Danilo Brajovic, David A. Kreplin, Marco F. HuberHeterogeneous Pruning Scores Pruning
ReVision: Scaling Computer-Use Agents via Temporal Visual Redundancy Reduction
May 11, 2026Amirhossein Abaskohi, Yuhang He, Peter West +3Computer-Use Agents Multimodal Agents
RUBEN: Rule-Based Explanations for Retrieval-Augmented LLM Systems
May 11, 2026Joel Rorseth, Parke Godfrey, Lukasz Golab +2Large Language Model Safety Minimal
Beyond the Last Layer: Multi-Layer Representation Fusion for Visual Tokenization
May 11, 2026Xuanyu Zhu, Yan Bai, Yang Shi +4Vision Encoders Visual Tokens
Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice
May 11, 2026Xiusheng Huang, Xin Jiang, Jun Zhao +2Token Compression Visual Tokens
ERASE: Eliminating Redundant Visual Tokens via Adaptive Two-Stage Token Pruning
May 11, 2026Yuna Lee, Kyoungho Min, Yulhwa KimVisual Token Pruning Concept Erasure
PruneTIR: Inference-Time Tool Call Pruning for Effective yet Efficient Tool-Integrated Reasoning
May 11, 2026Luan Zhang, Dandan Song, Zhijing Wu +8Large Language Model Reasoning Fewer Tool-Call Errors
Evading Visual Aphasia: Contrastive Adaptive Semantic Token Pruning for Vision-Language Models
May 10, 2026Jie Ma, Yihang Liu, Zhike Qiu +2Visual Token Pruning Large Vision Language Models
Selection Plateau and a Sparsity-Dependent Hierarchy of Pruning Features
May 10, 2026Guangqi Li, Yongxin LiSparsity Pruning
Relative Kinetic Utility for Reasoning-Aware Structural Pruning in Large Language Models
May 9, 2026Tianhao QianHeterogeneous Pruning Scores Large Models
How Many Visual Tokens Do Multimodal Language Models Need? Scaling Visual Token Pruning with F^3A
May 9, 2026YiJie Huang, Yiqun Zhang, Zhuoyue Jia +7Visual Token Pruning Visual Tokens
Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning
May 9, 2026Chen Wang, Siyu Hu, Guangming Tan +1Equivariant Neural Networks Wireless Foundation Models
SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training
May 9, 2026Shengkun Tang, Zekun Wang, Bo Zheng +7Large Language Model Compression Large Language Model Pretraining

May 25, 2026 · cs.CVJ/K move · Enter open · S save

Channel-wise Vector Quantization

Wei Song, Tianhang Wang, Yitong Chen, Tong Zhang+4

We present Channel-wise Vector Quantization (CVQ), a novel image tokenization paradigm that replaces patch-wise tokens with channel-wise tokens. Unlike conventional vector quantization, which assigns a discrete token to each patch feature vector, CVQ quantizes each channel of the feature map. This formulation represents an image as discrete levels of visual details, rather than as a grid of spatial patches. Based on CVQ, we introduce a new visual autoregressive framework with "next-channel prediction". Instead of rendering images patch by patch in raster order, our Channel-wise Autoregressive (CAR) model predicts image channels sequentially, producing progressively enriched visual details. Specifically, it first sketches global structure and then refines fine-grained attributes, akin to a human artist's workflow. Empirically, we show that: (1) CVQ achieves 100% codebook utilization with a 16K+ codebook size without any bells and whistles, and substantially improves reconstruction quality over conventional VQ; and (2) CAR attains a DPG score of 86.7 and a GenEval score of 0.79, demonstrating strong effectiveness for text-to-image generation.

Autoregressive Image Generation Visual Tokens Calibration-Free Low-Bit Vector Quantization Autoregressive Model Quantization

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