{"total":60,"rows":[{"id":"2502.02175","title":"VLA-Cache: Efficient Vision-Language-Action Manipulation via Adaptive Token Caching","created":"2025-02-04","cited_by_count":86,"area":"lr"},{"id":"2507.13348","title":"VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning","created":"2025-07-17","cited_by_count":43,"area":"lr"},{"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":"2503.17349","title":"Beyond Semantics: Rediscovering Spatial Awareness in Vision-Language Models","created":"2025-03-21","cited_by_count":37,"area":"lr"},{"id":"2503.13360","title":"Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning","created":"2025-03-17","cited_by_count":32,"area":"lr"},{"id":"2505.23727","title":"PixelThink: Towards Efficient Chain-of-Pixel Reasoning","created":"2025-05-29","cited_by_count":28,"area":"lr"},{"id":"2509.25848","title":"More Thought, Less Accuracy? On the Dual Nature of Reasoning in Vision-Language Models","created":"2025-09-30","cited_by_count":27,"area":"lr"},{"id":"2506.21710","title":"FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering","created":"2025-06-26","cited_by_count":20,"area":"lr"},{"id":"2407.00468","title":"MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation","created":"2024-06-29","cited_by_count":18,"area":"lr"},{"id":"2412.03409","title":"PrefixKV: Adaptive Prefix KV Cache is What Vision Instruction-Following Models Need for Efficient Generation","created":"2024-12-04","cited_by_count":13,"area":"lr"},{"id":"2503.10905","title":"Learning to Inference Adaptively for Multimodal Large Language Models","created":"2025-03-13","cited_by_count":12,"area":"lr"},{"id":"2507.01513","title":"SafePTR: Token-Level Jailbreak Defense in Multimodal LLMs via Prune-then-Restore Mechanism","created":"2025-07-02","cited_by_count":10,"area":"lr"},{"id":"2607.24904","title":"Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model","created":"2026-07-27","cited_by_count":10,"area":"lr"},{"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":"2509.06461","title":"Focusing by Contrastive Attention: Enhancing VLMs' Visual Reasoning","created":"2025-09-08","cited_by_count":8,"area":"lr"},{"id":"2512.18910","title":"Delta-LLaVA: Base-then-Specialize Alignment for Token-Efficient Vision-Language Models","created":"2025-12-21","cited_by_count":7,"area":"lr"},{"id":"2605.05126","title":"ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation","created":"2026-05-06","cited_by_count":6,"area":"lr"},{"id":"2605.22269","title":"MuKV: Multi-Grained KV Cache Compression for Long Streaming Video Question-Answering","created":"2026-05-21","cited_by_count":6,"area":"lr"},{"id":"2501.09532","title":"AdaFV: Rethinking of Visual-Language alignment for VLM acceleration","created":"2025-01-16","cited_by_count":4,"area":"lr"},{"id":"2509.24837","title":"ZOO-Prune: Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models","created":"2025-09-29","cited_by_count":4,"area":"lr"},{"id":"2606.11576","title":"AVIS: Adaptive Test-Time Scaling for Vision-Language Models","created":"2026-06-10","cited_by_count":4,"area":"lr"},{"id":"2504.19627","title":"VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning","created":"2025-04-28","cited_by_count":3,"area":"lr"},{"id":"2509.13067","title":"HERO: Rethinking Visual Token Early Dropping in High-Resolution Large Vision-Language Models","created":"2025-09-16","cited_by_count":3,"area":"lr"},{"id":"2602.20205","title":"OTPrune: Distribution-Aligned Visual Token Pruning via Optimal Transport","created":"2026-02-22","cited_by_count":3,"area":"lr"},{"id":"2603.21701","title":"Rethinking Token Reduction for Large Vision-Language Models","created":"2026-03-23","cited_by_count":3,"area":"lr"},{"id":"2608.09682","title":"Thinking With Tools, Not With Pixels: Tool Calls as Text Scaffolds for Visual Reasoning","created":"2026-08-10","cited_by_count":3,"area":"lr"},{"id":"2602.18846","title":"DUET-VLM: Dual stage Unified Efficient Token reduction for VLM Training and Inference","created":"2026-02-21","cited_by_count":2,"area":"lr"},{"id":"2603.27375","title":"Bridging Visual Representation and Reinforcement Learning from Verifiable Rewards in Large Vision-Language Models","created":"2026-03-28","cited_by_count":2,"area":"lr"},{"id":"2605.19322","title":"DynaTok: Temporally Adaptive and Positional Bias-Aware Token Compression for Video-LLMs","created":"2026-05-19","cited_by_count":2,"area":"lr"},{"id":"2607.12815","title":"Visual Access Boundaries in Vision-Language Model Reasoning","created":"2026-07-14","cited_by_count":2,"area":"lr"},{"id":"2608.04132","title":"RUTA: Principled Visual Token Allocation via Rate-Utility Optimization","created":"2026-08-04","cited_by_count":2,"area":"lr"},{"id":"2412.09817","title":"Enhancing Multimodal Large Language Models Complex Reason via Similarity Computation","created":"2024-12-13","cited_by_count":1,"area":"lr"},{"id":"2510.09189","title":"LLaMAX2: Your Translation-Enhanced Model also Performs Well in Reasoning","created":"2025-10-10","cited_by_count":1,"area":"lr"},{"id":"2601.13797","title":"PREGEN: Uncovering Latent Thoughts in Composed Video Retrieval","created":"2026-01-20","cited_by_count":1,"area":"lr"},{"id":"2603.22815","title":"Focus, Don't Prune: Identifying Instruction-Relevant Regions for Information-Rich Image Understanding","created":"2026-03-24","cited_by_count":1,"area":"lr"},{"id":"2603.26365","title":"Dynamic Token Compression for Efficient Video Understanding through Reinforcement Learning","created":"2026-03-27","cited_by_count":1,"area":"lr"},{"id":"2604.13268","title":"Indexing Multimodal Language Models for Large-scale Image Retrieval","created":"2026-04-14","cited_by_count":1,"area":"lr"},{"id":"2605.28160","title":"Look on Demand: A Cognitive Scheduling Framework for Visual Evidence Acquisition in Multimodal Reasoning","created":"2026-05-27","cited_by_count":1,"area":"lr"},{"id":"2606.02842","title":"Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning","created":"2026-06-01","cited_by_count":1,"area":"lr"},{"id":"2606.24165","title":"Spectral Evolution-Guided Token Pruning in Multimodal Large Language Models","created":"2026-06-23","cited_by_count":1,"area":"lr"},{"id":"2607.01707","title":"LASER: A Corrective Lens for LVLMs via Visual Attention Preservation and Sink Suppression","created":"2026-07-02","cited_by_count":1,"area":"lr"},{"id":"2607.20357","title":"Look Less, Think Faster: Joint Token-Compute Adaptation for Multimodal LLMs","created":"2026-07-22","cited_by_count":1,"area":"lr"},{"id":"2608.04610","title":"HiSC: Hierarchical Spatial Clustering Token Compression for Efficient 3D Scene Understanding","created":"2026-08-05","cited_by_count":1,"area":"lr"},{"id":"2608.13226","title":"CoverPrune: Coverage-Driven Token Pruning for 3D VLMs via Optimal Transport","created":"2026-08-13","cited_by_count":1,"area":"lr"},{"id":"2608.29208","title":"AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models","created":"2026-08-29","cited_by_count":1,"area":"lr"},{"id":"2610.04318","title":"Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End Latency","created":"2026-10-03","cited_by_count":1,"area":"lr"},{"id":"2511.18875","title":"Parallel Vision Token Scheduling for Fast and Accurate Multimodal LMMs Inference","created":"2025-11-24","cited_by_count":0,"area":"lr"},{"id":"2603.27960","title":"Towards Efficient Large Vision-Language Models: A Comprehensive Survey on Inference Strategies","created":"2026-03-30","cited_by_count":0,"area":"lr"},{"id":"2603.29405","title":"Hallucination-aware intermediate representation edit in large vision-language models","created":"2026-03-31","cited_by_count":0,"area":"lr"},{"id":"2604.02689","title":"Efficient3D: A Unified Framework for Adaptive and Debiased Token Reduction in 3D MLLMs","created":"2026-04-03","cited_by_count":0,"area":"lr"},{"id":"2606.31599","title":"Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning","created":"2026-06-30","cited_by_count":0,"area":"lr"},{"id":"2607.00465","title":"StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning","created":"2026-07-01","cited_by_count":0,"area":"lr"},{"id":"2608.01185","title":"3DZip: Spatial-Aware Feature Diversity-Guided Token Compression for 3D Question Answering","created":"2026-08-02","cited_by_count":0,"area":"lr"},{"id":"2609.26484","title":"From Token Importance to Conditional Removability: Rethinking Visual Token Pruning in Multimodal Large Language Models","created":"2026-09-22","cited_by_count":0,"area":"lr"},{"id":"2609.29601","title":"Free the Language Model From the Vision Encoder: Semantic Serialization as a Perception Interface for Small Language Models","created":"2026-08-29","cited_by_count":0,"area":"lr"},{"id":"2609.34044","title":"SCOPD: Sparse-Context On-Policy Self-Distillation for Efficient Vision-Language Models","created":"2026-09-28","cited_by_count":0,"area":"lr"},{"id":"2609.35394","title":"Rethinking Visual Token Compression for Video Large Language Models: A Simple Yet Strong Baseline","created":"2026-09-28","cited_by_count":0,"area":"lr"},{"id":"2609.38098","title":"NeuronEye: Query-Guided Visual Concept Activation for Vision-Language Reasoning","created":"2026-09-29","cited_by_count":0,"area":"lr"},{"id":"2610.11111","title":"Lapras: Latent Reasoning for Time Series Language Models","created":"2026-10-08","cited_by_count":0,"area":"lr"},{"id":"2610.16615","title":"When 1+1 Backfires: Rethinking Relevance-Diversity Balancing for Sample-Aware Visual Token Reduction","created":"2026-10-12","cited_by_count":0,"area":"lr"}],"next_cursor":null}