Vision Transformer

Also known as ViT

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Latest papers 350

50 papers in the last four weeks, up 39% on the four weeks before. 0.3% of all new papers.

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Scaling Vision Transformers Without Training: Prune-and-Merge Token Compression
Oct 13, 2026Vatsal, Soumil Malhotra, Priyanshu Chahal +1Vision Transformer Efficient ViTs
Department of Mathematics, Indian Institute of Technology Roorkee
Bottlenecked semantic compression by representation reconstruction
Oct 12, 2026Xiaoya Tang, Shilong Liu, Daniel Smolyak +3Visual Token Compression Efficient ViTs
Scientific Computing and Imaging Institute University of Utah · Princeton AI Lab Princeton University · National Institutes of Health
ChangeT $^3$ : Evaluating Vision Test-Time Training for Remote Sensing Change Detection
Oct 11, 2026Sharukshan Niranjan, Oshadha Samarakoon, Nichula Wasalathilaka +3Remote Sensing Change Detection Test-Time Training
University of Peradeniya, Peradeniya, Sri Lanka
Event-based Action Recognition by Pre-Training on Multi-Frame Representations
Oct 9, 2026Emma Norrby, Tomas Wilkinson, Per Nyblom +1Event-Based Vision Masked Autoencoders
Swedish Defence Research Agency (FOI), Linköping, Sweden
Decoding Register Tokens Preserves Global Scene Details
Oct 9, 2026David Jacob Drexlin, Julius Hense, Jonas DippelVision Transformer Image Reconstruction
Machine Learning Group, Technische Universität Berlin · BIFOLD – Berlin Institute for the Foundations of Learning and Data Franklinstraße 28/29, 10587 Berlin, Germany · Aignostics, Germany
Vision Transformers Learn Word Meaning from Images Alone
Oct 9, 2026Anders Gjølbye, Sebastian Ray Mason, Stella Frank +1Vision Transformer Vision-Language Alignment
Department of Applied Mathematics and Computer Science Technical University of Denmark
Learning Features, Not Layouts: Feature-Axis Attention as a Transfer Prior for Medical Imaging
Oct 9, 2026Aon Safdar, Mohamed SaadeldinMedical Image Representation Learning Vision Transformer
University College Dublin, Ireland
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation
Oct 8, 2026Marco Stefani, Edoardo Parpaiola, Matteo Bino +5Neural Network Interpretability Saliency Map Evaluation
Department of Information Engineering (DEI), University of Padova, Padova, Italy
Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study
Oct 8, 2026Kim-Cuc Nguyen, Ngai-Man CheungVision Transformer Neural Network Generalization
Temasek Laboratories Singapore University of Technology and Design Singapore
Region-Aware CLS Token Augmentation for Fine-Grained Image Retrieval
Oct 7, 2026Ian de Holanda Cavalcanti Bezerra, Vivek Trivedy, Lucas Pascotti Valem +1Fine-Grained Image Retrieval Image Retrieval
Institute of Mathematics and Computer Science (ICMC), University of S˜ao Paulo (USP), S˜ao Carlos, Brazil · Department of Computer and Information Science, Temple University, Philadelphia, PA, USA
On the Necessity of Attention-FFN Split in Vision Transformers
Oct 7, 2026Junhyeok Kim, Jinyeong Kim, Jae Wan Park +1Vision Transformer Attention Mechanisms
Department of Artificial Intelligence, Yonsei University, Seoul, Republic of Korea.
Test-Time Adaptation of Quantized ViTs via Single-Pass Quantizer-Aligned Recalibration
Oct 6, 2026Hyeongheon Cha, Young D. Kwon, Sung-Ju LeeTest-Time Adaptation Vision Transformer
KAIST · Samsung AI Center-Cambridge · University of Cambridge
Emoception: Selective Affective Layer Fine-Tuning of Video Vision Transformers for Player Arousal Change Recognition From Gameplay Footage
Oct 6, 2026Yi Xia, Ibrahim Khan, Mury Fajar Dewantoro +2Vision Transformer Affective Computing
Graduate School of Information Science and Engineering, Ritsumeikan University, Osaka, Japan · College of Information Science and Engineering, Ritsumeikan University, Osaka, Japan · Alumni Association of Carnegie Mellon University, Pittsburgh, PA, USA
REViT-v2: Hierarchical Windowed Roto-reflection Equivariant ViT for Equivariant Feature Extraction
Oct 6, 2026Sheir A. Zaheer, Jihwan Moon, Chan Y. ParkVision Transformer Equivariant Neural Networks
KC Machine Learning Lab, Rep. of Korea · NFOCZ Inc and Seoul National University, Rep. of Korea
Vision Transformer Ensembles for Panoramic Street Segmentation
Oct 5, 2026Yunus Serhat BıçakçıEnsemble Learning Vision Transformer
Department of Artificial Intelligence and Machine Learning, Faculty of Applied Sciences, Marmara University, Istanbul, Türkiye · Geospatial Data Science Group, School of Geographical and Earth Sciences, University of Glasgow, Glasgow, UK
FLASHSWIN: Unlocking Large Windows and Dense Tokens in Swin Vision Transformers with Memory Efficient Attention
Oct 3, 2026Tushar Kataria, Gerald Sabin, Ponnuswamy Sadayappan +1Vision Transformer Efficient ViTs
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA · Kahlert School of Computing, University of Utah, Salt Lake City, UT, USA · RNET Technologies, Dayton, OH, USA
RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers
Oct 3, 2026Mengyuan Fan, Bokai Huang, JiaMing Pan +4Low-Bit Quantization Rotation-Based Quantization
Peking University
Synthetic-to-Real ViT-Based Pose Estimation of a Noncooperative UAV
Oct 3, 2026Krishnanujam Srinivas, Hanish Acharla, Brij Agrawal +1Object Pose Estimation Synthetic-to-Real Domain Adaptation
Spacecraft Research and Design Center, Department of Mechanical and Aerospace Engineering, Naval Postgraduate School, Monterey.
Metonymic Circuits for Abstract Concept Grounding in Vision Transformers
Oct 3, 2026Jing Ding, Ziqiao Ma, Jiayuan Mao +2VLM Interpretability Vision Transformer
University of Michigan · Vector Institute · University of Pennsylvania +2
Dynamic Quadtree Tokenization and Transformer for Adaptive Mesh PDE Forecasting
Oct 2, 2026Yilin Zhuang, Noah Zambrano, Karthik DuraisamyPDE Surrogate Modeling Vision Transformer
Department of Aerospace Engineering University of Michigan Ann Arbor, MI 48105 · University of Michigan Ann Arbor, MI 48105
MAGEFormer: Learning Metric-Consistent Representations for Anisotropic CT Segmentation
Oct 2, 2026Jiaying Li, Paolo RemagninoMedical Image Segmentation 3D Medical Image Segmentation
Department of Computer Science, Durham University, Durham, UK
Decoding the Functional Roles of Register and High-Norm Patch Tokens in Vision Transformers
Oct 2, 2026Neel Varma, Andrew Rufail, Dipika Khullar +1Vision Transformer Transformer Interpretability
Two Routes to the Middle: Placement Search and Brain Readouts Converge on Where Continual Learners Should Specialize
Oct 1, 2026Yuan Huang, Zihan Chen, Runbin Zhang +3Vision Transformer Low-Rank Adaptation
Northeastern University
Curvature Under Attack in hZACH-ViT: Gauge Symmetry, Boundary Saturation, and Adversarial Failure
Sep 30, 2026Athanasios Angelakis, Marta Gomez-BarreroVision Transformer Adversarial Robustness
BioML, Research Institute CODE, University of the Bundeswehr Munich, Munich, Germany · Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
FAST: Flow Any Scene Transformer
Sep 30, 2026Yongjian Zhang, Longguang Wang, Zhuo Song +3Optical Flow Vision Transformer
School of Electronics and Communication Engineering, the Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China · Hong Kong Polytechnic University, HKSAR, China · School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
Routing Probes Can Improve Without New Information: An Exact-Null Audit of Uncertainty Beyond Model Outputs
Sep 30, 2026Wenhao Liang, Lin Yue, Wei Emma Zhang +3Vision Transformer Statistical Hypothesis Testing
Procedural Core: A Compact Recurrent Initialization for Vision Transformers
Sep 29, 2026Zachary Shinnick, Christian Internò, Hemanth Saratchandran +2Neural Network Initialization Vision Transformer
Australian Institute for Machine Learning (AIML), Adelaide University · Bielefeld University · Metacognition AI +1
Energy Variation in Training Modern Computer Vision Architectures
Sep 29, 2026David Cortes, Carlos Juiz, Belen BermejoEnergy-Efficient ML Vision Transformer
University of the Balearic Islands (Spain)
Learned Queries and Keys Are All You Need: Replacing the Value Projection with Structured Transforms
Sep 29, 2026Ene Meco, Emadeldeen Hamdan, A. Enis CetinTransformer Attention Efficient ViTs
University of Illinois Chicago, Chicago, IL 60607
Copy the Same, Distill the Difference: Initializing Linear Vision Transformers
Sep 28, 2026Huaiyuan Qin, Muli Yang, Gabriel James Goenawan +9Neural Network Initialization Vision Transformer
Institute of Advanced Intelligence and Computing (IAIC), A*STAR, Singapore · Nanyang Technological University · ST Engineering Geo-Insights, Singapore +3

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Scaling Vision Transformers Without Training: Prune-and-Merge Token Compression

Vatsal, Soumil Malhotra, Priyanshu Chahal, Sanjeev Kumar

Department of Mathematics, Indian Institute of Technology Roorkee

Vision Transformer Efficient ViTs Visual Token Compression Visual Token Pruning Visual Token Merging

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Vision Transformers achieve strong performance but incur high computational costs from quadratic token interactions. Training-free token reduction methods improve efficiency, but their robustness remains underexplored. We propose Prune-and Merge ViT, a training-free framework for off-the-shelf models. It combines class attention-based pruning with similarity-based merging to reduce redundancy while preserving semantic information. To evaluate robustness we introduce two metrics. Relative Accuracy Drop (RAD) measures relative accuracy degradation under transformations, and Prediction Flip Rate (PFR) quantifies prediction consistency. On pretrained ViT and DeiT, Prune-and-Merge reduces computation competitively while maintaining robustness and better accuracy than existing token reduction methods. Our analysis suggests that hybrid token reduction does not introduce hallucination-like behavior and preserves prediction stability for common image transformations.