{"total":155,"rows":[{"id":"2504.17343","title":"TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming Videos","created":"2025-04-24","cited_by_count":97,"area":null},{"id":"2506.10967","title":"Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs","created":"2025-06-12","cited_by_count":96,"area":"mllm"},{"id":"2506.10100","title":"EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models","created":"2025-06-11","cited_by_count":93,"area":"vla"},{"id":"2503.14905","title":"Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation","created":"2025-03-19","cited_by_count":68,"area":"mllm"},{"id":"2510.02912","title":"Don't Just Chase \"Highlighted Tokens\" in MLLMs: Revisiting Visual Holistic Context Retention","created":"2025-10-03","cited_by_count":47,"area":"mllm"},{"id":"2505.22654","title":"VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models","created":"2025-05-28","cited_by_count":41,"area":"lr"},{"id":"2509.07979","title":"Visual Representation Alignment for Multimodal Large Language Models","created":"2025-09-09","cited_by_count":41,"area":"lr"},{"id":"2505.14454","title":"Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models","created":"2025-05-20","cited_by_count":38,"area":"inference"},{"id":"2512.00891","title":"Accelerating Streaming Video Large Language Models via Hierarchical Token Compression","created":"2025-11-30","cited_by_count":37,"area":"inference"},{"id":"2505.19147","title":"Shifting AI Efficiency From Model-Centric to Data-Centric Compression","created":"2025-05-25","cited_by_count":29,"area":"mllm"},{"id":"2509.01552","title":"Variation-aware Vision Token Dropping for Faster Large Vision-Language Models","created":"2025-09-01","cited_by_count":27,"area":"mllm"},{"id":"2510.00515","title":"Efficient Multi-modal Large Language Models via Progressive Consistency Distillation","created":"2025-10-01","cited_by_count":22,"area":"mllm"},{"id":"2510.07293","title":"AudioMarathon: A Comprehensive Benchmark for Long-Context Audio Understanding and Efficiency in Audio LLMs","created":"2025-10-08","cited_by_count":22,"area":"inference"},{"id":"2507.23318","title":"FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning","created":"2025-07-31","cited_by_count":20,"area":"vla"},{"id":"2506.00993","title":"FlexSelect: Flexible Token Selection for Efficient Long Video Understanding","created":"2025-06-01","cited_by_count":18,"area":null},{"id":"2508.07871","title":"CATP: Contextually Adaptive Token Pruning for Efficient and Enhanced Multimodal In-Context Learning","created":"2025-08-11","cited_by_count":18,"area":"mllm"},{"id":"2510.07143","title":"Are We Using the Right Benchmark: An Evaluation Framework for Visual Token Compression Methods","created":"2025-10-08","cited_by_count":17,"area":"mllm"},{"id":"2508.13305","title":"Prune2Drive: A Plug-and-Play Framework for Accelerating Vision-Language Models in Autonomous Driving","created":"2025-08-18","cited_by_count":16,"area":"mllm"},{"id":"2512.06866","title":"Less Is More, but Where? Dynamic Token Compression via LLM-Guided Keyframe Prior","created":"2025-12-07","cited_by_count":15,"area":"inference"},{"id":"2509.21789","title":"Visual Multi-Agent System: Mitigating Hallucination Snowballing via Visual Flow","created":"2025-09-26","cited_by_count":13,"area":"mllm"},{"id":"2511.02650","title":"Can Visual Input Be Compressed? A Visual Token Compression Benchmark for Large Multimodal Models","created":"2025-11-04","cited_by_count":13,"area":"mllm"},{"id":"2503.09387","title":"VideoScan: Enabling Efficient Streaming Video Understanding via Frame-level Semantic Carriers","created":"2025-03-12","cited_by_count":12,"area":"mllm"},{"id":"2512.07580","title":"When Token Pruning is Worse than Random: Understanding Visual Token Information in VLLMs","created":"2025-12-08","cited_by_count":12,"area":"inference"},{"id":"2602.19870","title":"ApET: Approximation-Error Guided Token Compression for Efficient VLMs","created":"2026-02-23","cited_by_count":12,"area":"mllm"},{"id":"2505.10118","title":"Why 1 + 1 < 1 in Visual Token Pruning: Beyond Naive Integration via Multi-Objective Balanced Covering","created":"2025-05-15","cited_by_count":11,"area":"inference"},{"id":"2510.16598","title":"VisionSelector: End-to-End Learnable Visual Token Compression for Efficient Multimodal LLMs","created":"2025-10-18","cited_by_count":11,"area":"mllm"},{"id":"2603.07135","title":"The Model Knows Which Tokens Matter: Automatic Token Selection via Noise Gating","created":"2026-03-07","cited_by_count":11,"area":"mllm"},{"id":"2605.09649","title":"Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction","created":"2026-05-10","cited_by_count":11,"area":"inference"},{"id":"2602.07574","title":"ViCA: Efficient Multimodal LLMs with Vision-Only Cross-Attention","created":"2026-02-07","cited_by_count":10,"area":"mllm"},{"id":"2604.05546","title":"Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects","created":"2026-04-07","cited_by_count":9,"area":"lr"},{"id":"2604.09000","title":"StreamMeCo: Long-Term Agent Memory Compression for Efficient Streaming Video Understanding","created":"2026-04-10","cited_by_count":9,"area":null},{"id":"2604.23950","title":"LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models","created":"2026-04-27","cited_by_count":9,"area":"lr"},{"id":"2505.16175","title":"QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design","created":"2025-05-22","cited_by_count":8,"area":null},{"id":"2508.03351","title":"SalQ-VLM: Fine-Grained Saliency-Guided Quantization for Vision-Language Models","created":"2025-08-05","cited_by_count":8,"area":"mllm"},{"id":"2509.23873","title":"Winning the Pruning Gamble: A Unified Approach to Joint Sample and Token Pruning for Efficient Supervised Fine-Tuning","created":"2025-09-28","cited_by_count":8,"area":"alignment"},{"id":"2601.19325","title":"Innovator-VL: A Multimodal Large Language Model for Scientific Discovery","created":"2026-01-27","cited_by_count":8,"area":"mllm"},{"id":"2505.18757","title":"ToDRE: Effective Visual Token Pruning via Token Diversity and Task Relevance","created":"2025-05-24","cited_by_count":7,"area":"mllm"},{"id":"2508.09981","title":"LLMC+: Benchmarking Vision-Language Model Compression with a Plug-and-play Toolkit","created":"2025-08-13","cited_by_count":7,"area":"mllm"},{"id":"2512.19443","title":"D2Pruner: Debiased Importance and Structural Diversity for MLLM Token Pruning","created":"2025-12-22","cited_by_count":7,"area":"mllm"},{"id":"2512.02700","title":"VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm","created":"2025-12-02","cited_by_count":6,"area":"mllm"},{"id":"2602.21233","title":"AngelSlim: A more accessible, comprehensive, and efficient toolkit for large model compression","created":"2026-02-07","cited_by_count":6,"area":"inference"},{"id":"2603.21957","title":"Unified Spatiotemporal Token Compression for Video-LLMs at Ultra-Low Retention","created":"2026-03-23","cited_by_count":6,"area":"inference"},{"id":"2606.24422","title":"EgoSAT: A Comprehensive Benchmark of Egocentric Streaming Interaction Understanding","created":"2026-06-23","cited_by_count":6,"area":"mllm"},{"id":"2512.18747","title":"IPCV: Information-Preserving Compression for MLLM Visual Encoders","created":"2025-12-21","cited_by_count":5,"area":"mllm"},{"id":"2602.13315","title":"IDPruner: Harmonizing Importance and Diversity in Visual Token Pruning for MLLMs","created":"2026-02-10","cited_by_count":5,"area":"mllm"},{"id":"2603.01400","title":"Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models","created":"2026-03-02","cited_by_count":5,"area":"inference"},{"id":"2603.03681","title":"EvoPrune: Early-Stage Visual Token Pruning for Efficient MLLMs","created":"2026-03-04","cited_by_count":5,"area":"mllm"},{"id":"2604.17087","title":"EvoComp: Learning Visual Token Compression for Multimodal Large Language Models via Semantic-Guided Evolutionary Labeling","created":"2026-04-18","cited_by_count":5,"area":"mllm"},{"id":"2605.10343","title":"EvoStreaming: Your Offline Video Model Is a Natively Streaming Assistant","created":"2026-05-11","cited_by_count":5,"area":null},{"id":"2606.01711","title":"Improving Visual Token Reduction via Rectifying Distortions for Efficient Multimodal LLM Inference","created":"2026-06-01","cited_by_count":5,"area":"mllm"},{"id":"2606.16067","title":"Stepwise Token Selection for Efficient Multimodal Large Language Models","created":"2026-06-14","cited_by_count":5,"area":"mllm"},{"id":"2607.14557","title":"Seeing the End at Step Zero: Accelerating Diffusion MLLMs via MLP Sparsity-Aware Truncation","created":"2026-07-16","cited_by_count":5,"area":"lr"},{"id":"2504.04653","title":"LEO-MINI: An Efficient Multimodal Large Language Model using Conditional Token Reduction and Mixture of Multi-Modal Experts","created":"2025-04-07","cited_by_count":4,"area":"mllm"},{"id":"2509.21991","title":"ERGO: Efficient High-Resolution Visual Understanding for Vision-Language Models","created":"2025-09-26","cited_by_count":4,"area":"mllm"},{"id":"2605.00392","title":"RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference","created":"2026-05-01","cited_by_count":4,"area":"inference"},{"id":"2607.16326","title":"CRISP: Pre-LLM Yet Text-Driven Visual Token Pruning for Efficient LVLM Inference","created":"2026-07-15","cited_by_count":4,"area":"mllm"},{"id":"2511.15098","title":"A Comprehensive Study on Visual Token Redundancy for Discrete Diffusion-based Multimodal Large Language Models","created":"2025-11-19","cited_by_count":3,"area":"mllm"},{"id":"2602.05809","title":"Focus-Scan-Refine: From Human Visual Perception to Efficient Visual Token Pruning","created":"2026-02-05","cited_by_count":3,"area":"mllm"},{"id":"2602.20566","title":"BFA++: Hierarchical Best-Feature-Aware Token Prune for Multi-View Vision Language Action Model","created":"2026-02-24","cited_by_count":3,"area":"mllm"},{"id":"2603.05663","title":"Keeping the Evidence Chain: Semantic Evidence Allocation for Training-Free Token Pruning in Video Temporal Grounding","created":"2026-03-05","cited_by_count":3,"area":"inference"},{"id":"2603.21232","title":"QMoP: Query Guided Mixture-of-Projector for Efficient Visual Token Compression","created":"2026-03-22","cited_by_count":3,"area":"mllm"},{"id":"2604.07812","title":"HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models","created":"2026-04-09","cited_by_count":3,"area":"mllm"},{"id":"2605.25179","title":"Locality Matters for Training-Free Audio Token Compression in Audio-Language Models","created":"2026-05-24","cited_by_count":3,"area":"inference"},{"id":"2605.29657","title":"OccamToken: Efficient VLM Inference with Training-Free and Budget-Adaptive Token Pruning","created":"2026-05-28","cited_by_count":3,"area":"mllm"},{"id":"2606.18681","title":"Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs","created":"2026-06-17","cited_by_count":3,"area":"mllm"},{"id":"2606.24156","title":"Accelerating Multimodal Large Language Models with Prior-Corrected Token Reduction","created":"2026-06-23","cited_by_count":3,"area":"mllm"},{"id":"2609.01004","title":"SinkPruner: Sink-Free Visual Token Pruning for Multimodal Large Language Models","created":"2026-09-01","cited_by_count":3,"area":"mllm"},{"id":"2503.08101","title":"Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning","created":"2025-03-11","cited_by_count":2,"area":null},{"id":"2505.12728","title":"SpecFLASH: A Latent-Guided Semi-autoregressive Speculative Decoding Framework for Efficient Multimodal Generation","created":"2025-05-19","cited_by_count":2,"area":"mllm"},{"id":"2506.00577","title":"Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs","created":"2025-05-31","cited_by_count":2,"area":"lr"},{"id":"2506.01097","title":"Task-Related Token Compression in Multimodal Large Language Models from an Explainability Perspective","created":"2025-06-01","cited_by_count":2,"area":"mllm"},{"id":"2506.13166","title":"GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models","created":"2025-06-16","cited_by_count":2,"area":"mllm"},{"id":"2507.02909","title":"Fine-grained Token Allocation Via Operation Pruning for Efficient MLLMs","created":"2025-06-24","cited_by_count":2,"area":"mllm"},{"id":"2509.19191","title":"Reading Images Like Texts: Sequential Image Understanding in Vision-Language Models","created":"2025-09-23","cited_by_count":2,"area":"mllm"},{"id":"2510.26213","title":"OmniDocLayout: Towards Diverse Document Layout Generation via Coarse-to-Fine LLM Learning","created":"2025-10-30","cited_by_count":2,"area":null},{"id":"2512.01949","title":"Script: Graph-Structured and Query-Conditioned Semantic Token Pruning for Multimodal Large Language Models","created":"2025-12-01","cited_by_count":2,"area":"mllm"},{"id":"2602.03295","title":"POP: Prefill-Only Pruning for Efficient Large Model Inference","created":"2026-02-03","cited_by_count":2,"area":"mllm"},{"id":"2602.04657","title":"TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models","created":"2026-02-04","cited_by_count":2,"area":"mllm"},{"id":"2603.21105","title":"ResPrune: Text-Conditioned Subspace Reconstruction for Visual Token Pruning in Large Vision-Language Models","created":"2026-03-22","cited_by_count":2,"area":"mllm"},{"id":"2604.01881","title":"HieraVid: Hierarchical Token Pruning for Fast Video Large Language Models","created":"2026-04-02","cited_by_count":2,"area":"inference"},{"id":"2604.03072","title":"MI-Pruner: Crossmodal Mutual Information-guided Token Pruner for Efficient MLLMs","created":"2026-04-03","cited_by_count":2,"area":"mllm"},{"id":"2604.04972","title":"RCP: Representation Consistency Pruner for Mitigating Distribution Shift in Large Vision-Language Models","created":"2026-04-04","cited_by_count":2,"area":"mllm"},{"id":"2606.01756","title":"EvoCut: Multi-Layer Evolution-Aware Visual Token Compression for Efficient Large Vision-Language Models","created":"2026-06-01","cited_by_count":2,"area":"mllm"},{"id":"2606.27161","title":"TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference","created":"2026-06-25","cited_by_count":2,"area":"lr"},{"id":"2606.31982","title":"ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs","created":"2026-06-30","cited_by_count":2,"area":"mllm"},{"id":"2607.02484","title":"Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning","created":"2026-07-02","cited_by_count":2,"area":"inference"},{"id":"2607.10640","title":"Spectral Heat Flow for Conservative Token Condensation in Vision-Language Models","created":"2026-07-12","cited_by_count":2,"area":"mllm"},{"id":"2607.22716","title":"Visual Token Compression Enhances Robustness of MLLMs","created":"2026-07-21","cited_by_count":2,"area":"mllm"},{"id":"2608.07088","title":"RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs","created":"2026-08-07","cited_by_count":2,"area":"mllm"},{"id":"2609.03158","title":"Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization","created":"2026-09-02","cited_by_count":2,"area":"mllm"},{"id":"2508.06084","title":"AdaptInfer: Adaptive Token Pruning for Vision-Language Model Inference with Dynamical Text Guidance","created":"2025-08-08","cited_by_count":1,"area":"lr"},{"id":"2509.13676","title":"Re-purposing SAM into Efficient Visual Projectors for MLLM-Based Referring Image Segmentation","created":"2025-09-17","cited_by_count":1,"area":"mllm"},{"id":"2509.17197","title":"SignalLLM: A General-Purpose LLM Agent Framework for Automated Signal Processing","created":"2025-09-21","cited_by_count":1,"area":"agents"},{"id":"2511.14169","title":"AdaTok: Adaptive Token Compression with Object-Aware Representations for Efficient Multimodal LLMs","created":"2025-11-18","cited_by_count":1,"area":"mllm"},{"id":"2603.11220","title":"Frequency-Modulated Visual Restoration for Matryoshka Large Multimodal Models","created":"2026-03-11","cited_by_count":1,"area":"mllm"},{"id":"2603.14549","title":"ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference","created":"2026-03-15","cited_by_count":1,"area":"mllm"},{"id":"2603.24680","title":"ReDiPrune: Relevance-Diversity Pre-Projection Token Pruning for Efficient Multimodal LLMs","created":"2026-03-25","cited_by_count":1,"area":"mllm"},{"id":"2603.24941","title":"Beyond Attention Magnitude: Leveraging Inter-layer Rank Consistency for Efficient Vision-Language-Action Models","created":"2026-03-26","cited_by_count":1,"area":"vla"},{"id":"2603.26041","title":"Where and How to Prune: An Empirical Study of Visual Token Pruning for GUI Agent Navigation","created":"2026-03-27","cited_by_count":1,"area":"agents"},{"id":"2604.11240","title":"Decoupled Similarity for Task-Aware Token Pruning in Large Vision-Language Models","created":"2026-04-13","cited_by_count":1,"area":"mllm"}],"next_cursor":"100"}