{"total":33,"rows":[{"id":"2502.17422","title":"MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMs","created":"2025-02-24","cited_by_count":176,"area":"mllm"},{"id":"2407.02392","title":"TokenPacker: Efficient Visual Projector for Multimodal LLM","created":"2024-07-02","cited_by_count":172,"area":"mllm"},{"id":"2412.01818","title":"Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs","created":"2024-12-02","cited_by_count":157,"area":"mllm"},{"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":"2411.14228","title":"FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression","created":"2024-11-21","cited_by_count":22,"area":"mllm"},{"id":"2601.22674","title":"VisionTrim: Unified Vision Token Compression for Training-Free MLLM Acceleration","created":"2026-01-30","cited_by_count":18,"area":"mllm"},{"id":"2503.21817","title":"Skip-Vision: Efficient and Scalable Acceleration of Vision-Language Models via Adaptive Token Skipping","created":"2025-03-26","cited_by_count":12,"area":"mllm"},{"id":"2602.03060","title":"IVC-Prune: Revealing the Implicit Visual Coordinates in LVLMs for Vision Token Pruning","created":"2026-02-03","cited_by_count":12,"area":"mllm"},{"id":"2503.06362","title":"Adaptive Audio-Visual Speech Recognition via Matryoshka-Based Multimodal LLMs","created":"2025-03-09","cited_by_count":11,"area":"mllm"},{"id":"2511.15690","title":"MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping","created":"2025-11-19","cited_by_count":11,"area":"mllm"},{"id":"2410.02745","title":"AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity","created":"2024-09-20","cited_by_count":9,"area":"mllm"},{"id":"2508.17807","title":"Attention Debiasing for Token Pruning in Vision Language Models","created":"2025-08-25","cited_by_count":4,"area":"mllm"},{"id":"2509.11815","title":"SpecVLM: Fast Speculative Decoding in Vision-Language Models","created":"2025-09-15","cited_by_count":4,"area":"mllm"},{"id":"2505.24208","title":"Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap","created":"2025-05-30","cited_by_count":3,"area":"mllm"},{"id":"2508.06038","title":"Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models","created":"2025-08-08","cited_by_count":3,"area":"mllm"},{"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":"2505.23004","title":"QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without Retraining","created":"2025-05-29","cited_by_count":2,"area":"mllm"},{"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":"2602.04864","title":"When LLaVA Meets Objects: Token Composition for Vision-Language-Models","created":"2026-02-04","cited_by_count":2,"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":"2603.13349","title":"MURE: Hierarchical Multi-Resolution Encoding via Vision-Language Models for Visual Document Retrieval","created":"2026-03-07","cited_by_count":1,"area":"mllm"},{"id":"2603.18004","title":"Unified Spatio-Temporal Token Scoring for Efficient Video VLMs","created":"2026-03-18","cited_by_count":1,"area":"mllm"},{"id":"2608.05707","title":"One Ranking, Any Budget: Matryoshka Evidence-to-Context Frame Selection for Long-Video Understanding","created":"2026-08-06","cited_by_count":1,"area":"mllm"},{"id":"2602.00946","title":"ConsensusDrop: Fusing Visual and Cross-Modal Saliency for Efficient Vision Language Models","created":"2026-02-01","cited_by_count":0,"area":"mllm"},{"id":"2605.00789","title":"Make Your LVLM KV Cache More Lightweight","created":"2026-05-01","cited_by_count":0,"area":"mllm"},{"id":"2606.00543","title":"ETC: Extreme Token Compression via Task-aware Visual Information Distillation in VLMs","created":"2026-05-30","cited_by_count":0,"area":"mllm"},{"id":"2606.31383","title":"MS-Resampler: Multi-Scope Visual Resampling for Efficient Multimodal LLMs","created":"2026-06-30","cited_by_count":0,"area":"mllm"},{"id":"2607.13500","title":"Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models","created":"2026-07-15","cited_by_count":0,"area":"mllm"},{"id":"2609.10346","title":"Beyond One-Size-Fits-All: Sample-Adaptive Strategy Routing for Vision Token Pruning in MLLMs","created":"2026-09-09","cited_by_count":0,"area":"mllm"},{"id":"2609.17443","title":"BrainFocus: EEG-Guided ROI Selection for Efficient Vision-Language Models","created":"2026-09-15","cited_by_count":0,"area":"mllm"},{"id":"2609.35232","title":"Beyond Selection: Token Parameterization for Extreme Visual Token Compression","created":"2026-09-28","cited_by_count":0,"area":"mllm"},{"id":"2610.07987","title":"VisionWeave: Weaving Elastic Visual Representations as a Native Capability of MLLMs","created":"2026-10-06","cited_by_count":0,"area":"mllm"},{"id":"2610.09703","title":"Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs","created":"2026-10-07","cited_by_count":0,"area":"mllm"}],"next_cursor":null}