{"total":38,"rows":[{"id":"2112.13890","title":"SPViT: Enabling Faster Vision Transformers via Soft Token Pruning","created":"2021-12-27","cited_by_count":167,"area":"inference"},{"id":"2304.10716","title":"Joint Token Pruning and Squeezing Towards More Aggressive Compression of Vision Transformers","created":"2023-04-21","cited_by_count":81,"area":"inference"},{"id":"2305.17997","title":"DiffRate : Differentiable Compression Rate for Efficient Vision Transformers","created":"2023-05-29","cited_by_count":77,"area":"inference"},{"id":"2308.04657","title":"Which Tokens to Use? Investigating Token Reduction in Vision Transformers","created":"2023-08-09","cited_by_count":60,"area":"inference"},{"id":"2306.07050","title":"Revisiting Token Pruning for Object Detection and Instance Segmentation","created":"2023-06-12","cited_by_count":50,"area":"inference"},{"id":"2211.08110","title":"HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers","created":"2022-11-15","cited_by_count":46,"area":"inference"},{"id":"2310.01812","title":"PPT: Token Pruning and Pooling for Efficient Vision Transformers","created":"2023-10-03","cited_by_count":38,"area":"inference"},{"id":"2209.13802","title":"Adaptive Sparse ViT: Towards Learnable Adaptive Token Pruning by Fully Exploiting Self-Attention","created":"2022-09-28","cited_by_count":35,"area":"inference"},{"id":"2307.10780","title":"Learned Thresholds Token Merging and Pruning for Vision Transformers","created":"2023-07-20","cited_by_count":21,"area":"inference"},{"id":"2412.10569","title":"Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers","created":"2024-12-13","cited_by_count":21,"area":"inference"},{"id":"2311.03035","title":"GTP-ViT: Efficient Vision Transformers via Graph-based Token Propagation","created":"2023-11-06","cited_by_count":19,"area":"inference"},{"id":"2412.00965","title":"Token Cropr: Faster ViTs for Quite a Few Tasks","created":"2024-12-01","cited_by_count":19,"area":"inference"},{"id":"2506.20066","title":"ToSA: Token Merging with Spatial Awareness","created":"2025-06-24","cited_by_count":11,"area":"inference"},{"id":"2309.15755","title":"CAIT: Triple-Win Compression towards High Accuracy, Fast Inference, and Favorable Transferability For ViTs","created":"2023-09-27","cited_by_count":9,"area":"inference"},{"id":"2409.00633","title":"Make Your ViT-based Multi-view 3D Detectors Faster via Token Compression","created":"2024-09-01","cited_by_count":9,"area":"inference"},{"id":"2506.05709","title":"Token Transforming: A Unified and Training-Free Token Compression Framework for Vision Transformer Acceleration","created":"2025-06-06","cited_by_count":9,"area":"inference"},{"id":"2408.06798","title":"Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuning","created":"2024-08-13","cited_by_count":6,"area":"inference"},{"id":"2306.04897","title":"Multi-Scale And Token Mergence: Make Your ViT More Efficient","created":"2023-06-08","cited_by_count":5,"area":"inference"},{"id":"2403.14047","title":"Accelerating ViT Inference on FPGA through Static and Dynamic Pruning","created":"2024-03-21","cited_by_count":5,"area":"inference"},{"id":"2503.23455","title":"Efficient Token Compression for Vision Transformer with Spatial Information Preserved","created":"2025-03-30","cited_by_count":4,"area":"inference"},{"id":"2503.23459","title":"Reinforcement Learning-based Token Pruning in Vision Transformers: A Markov Game Approach","created":"2025-03-30","cited_by_count":3,"area":"inference"},{"id":"2505.15160","title":"Lossless Token Merging Even Without Fine-Tuning in Vision Transformers","created":"2025-05-21","cited_by_count":3,"area":"inference"},{"id":"2511.21477","title":"Frequency-Aware Token Reduction for Efficient Vision Transformer","created":"2025-11-26","cited_by_count":3,"area":"inference"},{"id":"2604.05718","title":"MPM: Mutual Pair Merging for Efficient Vision Transformers","created":"2026-04-07","cited_by_count":2,"area":"inference"},{"id":"2605.15852","title":"GHOST: Geometry-Hierarchical Online Streaming Token Eviction for Efficient 3D Reconstruction","created":"2026-05-15","cited_by_count":2,"area":"inference"},{"id":"2604.14563","title":"Revisiting Token Compression for Accelerating ViT-based Sparse Multi-View 3D Object Detectors","created":"2026-04-16","cited_by_count":1,"area":"inference"},{"id":"2605.27465","title":"AdaMerge: Salience-Aware Adaptive Token Merging for Training-Free Acceleration of Vision Transformers","created":"2026-05-26","cited_by_count":1,"area":"inference"},{"id":"2310.17177","title":"Bridging The Gaps Between Token Pruning and Full Pre-training via Masked Fine-tuning","created":"2023-10-26","cited_by_count":0,"area":"inference"},{"id":"2411.18092","title":"Training Noise Token Pruning","created":"2024-11-27","cited_by_count":0,"area":"inference"},{"id":"2509.14165","title":"Where Do Tokens Go? Understanding Pruning Behaviors in STEP at High Resolutions","created":"2025-09-17","cited_by_count":0,"area":"inference"},{"id":"2512.22760","title":"Neighbor-Aware Token Reduction via Hilbert Curve for Vision Transformers","created":"2025-12-28","cited_by_count":0,"area":"inference"},{"id":"2604.00827","title":"Video Patch Pruning: Efficient Video Instance Segmentation via Early Token Reduction","created":"2026-04-01","cited_by_count":0,"area":"inference"},{"id":"2604.16745","title":"Why Training-Free Token Reduction Collapses: The Inherent Instability of Pairwise Scoring Signals","created":"2026-04-17","cited_by_count":0,"area":"inference"},{"id":"2605.08371","title":"PrePARE: Pre-AA Token Pruning for Frozen Multi-View Geometry Transformers","created":"2026-05-08","cited_by_count":0,"area":"inference"},{"id":"2607.15563","title":"Are All Tokens Necessary for Visual Place Recognition? An Empirical Study of Token Reduction for Efficient Inference","created":"2026-07-17","cited_by_count":0,"area":"inference"},{"id":"2608.03681","title":"Keep the Needle, Prune the Haystack: Defect-Preserving Token Pruning for Efficient Zero-Shot Anomaly Detection","created":"2026-08-04","cited_by_count":0,"area":"inference"},{"id":"2608.10989","title":"Putting Registers to Work: Task Registers for Token Pruning in Vision Transformers","created":"2026-08-11","cited_by_count":0,"area":"inference"},{"id":"2608.22526","title":"RS$^3$-Prune: Read-Sparse, Store-Sparse Token Pruning for Video Object Segmentation","created":"2026-08-23","cited_by_count":0,"area":"inference"}],"next_cursor":null}