{"total":47,"rows":[{"id":"2505.18227","title":"Token Reduction Should Go Beyond Efficiency in Generative Models -- From Vision, Language to Multimodality","created":"2025-05-23","cited_by_count":50,"area":"inference"},{"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":"2412.20504","title":"ReTaKe: Reducing Temporal and Knowledge Redundancy for Long Video Understanding","created":"2024-12-29","cited_by_count":33,"area":"inference"},{"id":"2511.07278","title":"StreamKV: Streaming Video Question-Answering with Segment-based KV Cache Retrieval and Compression","created":"2025-11-10","cited_by_count":26,"area":"inference"},{"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":"2508.16201","title":"SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning","created":"2025-08-22","cited_by_count":20,"area":"inference"},{"id":"2602.08024","title":"FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging","created":"2026-02-08","cited_by_count":18,"area":"inference"},{"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":"2505.21233","title":"CROP: Contextual Region-Oriented Visual Token Pruning","created":"2025-05-27","cited_by_count":14,"area":"inference"},{"id":"2412.04652","title":"Cross-Self KV Cache Pruning for Efficient Vision-Language Inference","created":"2024-12-05","cited_by_count":12,"area":"inference"},{"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":"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":"2506.20066","title":"ToSA: Token Merging with Spatial Awareness","created":"2025-06-24","cited_by_count":11,"area":"inference"},{"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":"2512.12560","title":"StreamingAssistant: Efficient Visual Token Pruning for Accelerating Online Video Understanding","created":"2025-12-14","cited_by_count":10,"area":"inference"},{"id":"2509.09955","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","created":"2025-09-12","cited_by_count":7,"area":"inference"},{"id":"2510.07915","title":"MARC: Memory-Augmented RL Token Compression for Efficient Video Understanding","created":"2025-10-09","cited_by_count":6,"area":"inference"},{"id":"2512.10324","title":"EchoingPixels: Aliasing-Resistant Joint Token Reduction for Audio-Visual LLMs","created":"2025-12-11","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":"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":"2604.05650","title":"See the Forest for the Trees: Loosely Speculative Decoding via Visual-Semantic Guidance for Efficient Inference of Video LLMs","created":"2026-04-07","cited_by_count":5,"area":"inference"},{"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":"2605.30010","title":"EarlyTom: Early Token Compression Completes Fast Video Understanding","created":"2026-05-28","cited_by_count":4,"area":"inference"},{"id":"2504.18579","title":"Sparsity Forcing: Reinforcing Token Sparsity of MLLMs","created":"2025-04-23","cited_by_count":3,"area":"inference"},{"id":"2604.21335","title":"Sub-Token Routing for KV Cache Compression","created":"2026-04-23","cited_by_count":3,"area":"inference"},{"id":"2606.10533","title":"Audio-Visual Exchange-Aware Token Pruning for Efficient Audio-Visual Captioning","created":"2026-06-09","cited_by_count":3,"area":"inference"},{"id":"2503.23959","title":"Local Information Matters: Inference Acceleration For Grounded Conversation Generation Models Through Adaptive Local-Aware Token Pruning","created":"2025-03-31","cited_by_count":2,"area":"inference"},{"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":"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":"2603.11320","title":"UniCompress: Token Compression for Unified Vision-Language Understanding and Generation","created":"2026-03-11","cited_by_count":1,"area":"inference"},{"id":"2604.03414","title":"KiToke: Kernel-based Interval-aware Token Compression for Video Large Language Models","created":"2026-04-03","cited_by_count":1,"area":"inference"},{"id":"2605.10050","title":"EchoPrune: Interpreting Redundancy as Temporal Echoes for Efficient VideoLLMs","created":"2026-05-11","cited_by_count":1,"area":"inference"},{"id":"2607.23193","title":"OmniScope: Modality-Decoupled Token Compression for Omnimodal Large Language Models","created":"2026-07-25","cited_by_count":1,"area":"inference"},{"id":"2607.25669","title":"OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs","created":"2026-07-28","cited_by_count":1,"area":"inference"},{"id":"2608.01665","title":"Allocation Before Ranking: Decoupled Token Compression for OmniLLMs","created":"2026-08-03","cited_by_count":1,"area":"inference"},{"id":"2509.15250","title":"Walk and Read Less: Improving the Efficiency of Vision-and-Language Navigation via Tuning-Free Multimodal Token Pruning","created":"2025-09-18","cited_by_count":0,"area":"inference"},{"id":"2604.09547","title":"Tango: Taming Visual Signals for Efficient Video Large Language Models","created":"2026-04-10","cited_by_count":0,"area":"inference"},{"id":"2607.09080","title":"GeoTrace: Geometry-Aware Trajectory Token Compression for Video Large Language Models","created":"2026-07-10","cited_by_count":0,"area":"inference"},{"id":"2608.01638","title":"Dynamic Resolution Routing for Efficient Egocentric Grounding","created":"2026-08-03","cited_by_count":0,"area":"inference"},{"id":"2608.26142","title":"Position Is All You Need: A Free Lunch Token Compression Strategy for MLLM-based Referring Expression Segmentation","created":"2026-06-26","cited_by_count":0,"area":"inference"},{"id":"2609.08345","title":"CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs","created":"2026-09-08","cited_by_count":0,"area":"inference"},{"id":"2609.33397","title":"CoViST: Visual Token Compression via Composable States","created":"2026-09-27","cited_by_count":0,"area":"inference"},{"id":"2609.37042","title":"GleanVID: Complementary Token Selection for Efficient Video Large Language Models","created":"2026-09-29","cited_by_count":0,"area":"inference"},{"id":"2609.39704","title":"When Masking Helps or Hurts Robustness in Compressed CLIP: A Pre-Deployment Diagnostic","created":"2026-09-30","cited_by_count":0,"area":"inference"},{"id":"2610.16744","title":"FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models","created":"2026-10-12","cited_by_count":0,"area":"inference"},{"id":"2610.17355","title":"WIRE: Weight Space Implicit Representation Encoding of Frozen Video LLMs","created":"2026-10-12","cited_by_count":0,"area":"inference"},{"id":"2610.18690","title":"Just Respect the Semantics: Image-Token Compression via Pre-LLM Semantic Variable-Resolution Tokenization and In-LLM Relevance Pruning","created":"2026-10-13","cited_by_count":0,"area":"inference"}],"next_cursor":null}