{"total":63,"rows":[{"id":"2210.09461","title":"Token Merging: Your ViT But Faster","created":"2022-10-17","cited_by_count":1021,"area":"inference"},{"id":"2207.07061","title":"Confident Adaptive Language Modeling","created":"2022-07-14","cited_by_count":310,"area":"inference"},{"id":"2312.01026","title":"Token Fusion: Bridging the Gap between Token Pruning and Token Merging","created":"2023-12-02","cited_by_count":125,"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":"2305.17328","title":"Zero-TPrune: Zero-Shot Token Pruning through Leveraging of the Attention Graph in Pre-Trained Transformers","created":"2023-05-27","cited_by_count":62,"area":"inference"},{"id":"2308.01045","title":"Dynamic Token Pruning in Plain Vision Transformers for Semantic Segmentation","created":"2023-08-02","cited_by_count":62,"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":"2403.02991","title":"MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer","created":"2024-03-05","cited_by_count":54,"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":"2409.01156","title":"TempMe: Video Temporal Token Merging for Efficient Text-Video Retrieval","created":"2024-09-02","cited_by_count":40,"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":"2405.16148","title":"Accelerating Transformers with Spectrum-Preserving Token Merging","created":"2024-05-25","cited_by_count":35,"area":"inference"},{"id":"2406.09936","title":"ALGM: Adaptive Local-then-Global Token Merging for Efficient Semantic Segmentation with Plain Vision Transformers","created":"2024-06-14","cited_by_count":28,"area":"inference"},{"id":"2410.23782","title":"Video Token Merging for Long-form Video Understanding","created":"2024-10-31","cited_by_count":23,"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":"2412.00965","title":"Token Cropr: Faster ViTs for Quite a Few Tasks","created":"2024-12-01","cited_by_count":19,"area":"inference"},{"id":"2504.01690","title":"Token Pruning in Audio Transformers: Optimizing Performance and Decoding Patch Importance","created":"2025-04-02","cited_by_count":12,"area":"inference"},{"id":"2409.08464","title":"VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation","created":"2024-09-13","cited_by_count":11,"area":"inference"},{"id":"2506.20066","title":"ToSA: Token Merging with Spatial Awareness","created":"2025-06-24","cited_by_count":11,"area":"inference"},{"id":"2511.14751","title":"Co-Me: Confidence-Guided Token Merging for Visual Geometric Transformers","created":"2025-11-18","cited_by_count":10,"area":"inference"},{"id":"2405.14467","title":"Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation","created":"2024-05-23","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":"2406.07676","title":"FastAST: Accelerating Audio Spectrogram Transformer via Token Merging and Cross-Model Knowledge Distillation","created":"2024-06-11","cited_by_count":5,"area":"inference"},{"id":"2508.00367","title":"Representation Shift: Unifying Token Compression with FlashAttention","created":"2025-08-01","cited_by_count":5,"area":"inference"},{"id":"2408.17062","title":"Vote&Mix: Plug-and-Play Token Reduction for Efficient Vision Transformer","created":"2024-08-30","cited_by_count":4,"area":"inference"},{"id":"2412.08521","title":"EMS: Adaptive Evict-then-Merge Strategy for Head-wise KV Cache Compression Based on Global-Local Importance","created":"2024-12-11","cited_by_count":4,"area":"inference"},{"id":"2503.20282","title":"Faster Parameter-Efficient Tuning with Token Redundancy Reduction","created":"2025-03-26","cited_by_count":4,"area":"inference"},{"id":"2603.00527","title":"TP-Spikformer: Token Pruned Spiking Transformer","created":"2026-02-28","cited_by_count":4,"area":"inference"},{"id":"2303.02331","title":"Training-Free Acceleration of ViTs with Delayed Spatial Merging","created":"2023-03-04","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":"2505.20100","title":"AdaTP: Attention-Debiased Token Pruning for Video Large Language Models","created":"2025-05-26","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":"2512.20120","title":"HEART-VIT: Hessian-Guided Efficient Dynamic Attention and Token Pruning in Vision Transformer","created":"2025-12-23","cited_by_count":3,"area":"inference"},{"id":"2603.07307","title":"StructSAM: Structure- and Spectrum-Preserving Token Merging for Segment Anything Models","created":"2026-03-07","cited_by_count":2,"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":"2607.02612","title":"Fusion: A Framework for Unified Sequential Token AdaptatIon in VisiOn TraNsformers","created":"2026-07-01","cited_by_count":2,"area":"inference"},{"id":"2504.17996","title":"Back to Fundamentals: Low-Level Visual Features Guided Progressive Token Pruning","created":"2025-04-25","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":"2608.05217","title":"A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization","created":"2026-08-05","cited_by_count":1,"area":"inference"},{"id":"2404.09245","title":"Arena: A Patch-of-Interest ViT Inference Acceleration System for Edge-Assisted Video Analytics","created":"2024-04-14","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":"2507.09514","title":"QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models","created":"2025-07-13","cited_by_count":0,"area":"inference"},{"id":"2507.19409","title":"Modality Agnostic Efficient Long Range Encoder","created":"2025-07-25","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":"2604.16745","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":"2604.25421","title":"FED-FSTQ: Fisher-Guided Token Quantization for Communication-Efficient Federated Fine-Tuning of LLMs on Edge Devices","created":"2026-04-28","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":"2605.11683","title":"DORA: Dynamic Online Reinforcement Agent for Token Merging in Vision Transformers","created":"2026-05-12","cited_by_count":0,"area":"inference"},{"id":"2606.08156","title":"RAPID: Layer-Wise Redundancy-Aware Pruning and Importance-Driven Token Merging for Efficient ViT","created":"2026-06-06","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":"2608.28911","title":"SemKV: Semantic Mixed-Precision KV Cache Quantization Guided by the Quality Cliff for Long-Context LLM Inference","created":"2026-08-28","cited_by_count":0,"area":"inference"},{"id":"2609.03318","title":"Iapetus: Content-Aware Hierarchical Scheduling for Collaborative ViT Inference in LEO Satellite Networks","created":"2026-09-03","cited_by_count":0,"area":"inference"},{"id":"2609.13151","title":"Token Merging for Multilingual Speech Recognition: A Systematic Study Across Model Scale and Fine-Tuning","created":"2026-07-07","cited_by_count":0,"area":"inference"}],"next_cursor":null}