{"total":19,"rows":[{"id":"2510.02295","title":"VideoNSA: Native Sparse Attention Scales Video Understanding","created":"2025-10-02","cited_by_count":11,"area":"mllm"},{"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":"2509.16476","title":"Eye Gaze Tells You Where to Compute: Gaze-Driven Efficient VLMs","created":"2025-09-20","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":"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":"2607.23631","title":"PathSelect: Sequential Token Selection for Whole Slide Pathology","created":"2026-07-26","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":"2605.09429","title":"Evading Visual Aphasia: Contrastive Adaptive Semantic Token Pruning for Vision-Language Models","created":"2026-05-10","cited_by_count":1,"area":"mllm"},{"id":"2606.04911","title":"BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routine","created":"2026-06-03","cited_by_count":1,"area":"mllm"},{"id":"2608.01985","title":"DiffPrune: differentiable information throttling for token pruning in vision-language models","created":"2026-08-03","cited_by_count":1,"area":"mllm"},{"id":"2608.04496","title":"DIVE: Dynamic Iterative Visual Evidence Construction for Efficient Vision-Language Models","created":"2026-08-05","cited_by_count":1,"area":"mllm"},{"id":"2608.06411","title":"Learning to Predict Middle-Layer Attention in MLLMs for Visual Token Pruning","created":"2026-08-04","cited_by_count":1,"area":"mllm"},{"id":"2608.30263","title":"Centering before Pruning: Lightweight Geometry Correction for Diversity-Based Visual Token Pruning in LVLMs","created":"2026-08-31","cited_by_count":1,"area":"mllm"},{"id":"2609.19990","title":"QCPruner: Query-Conditioned Population Coverage for Visual Token Pruning","created":"2026-09-17","cited_by_count":1,"area":"mllm"},{"id":"2602.03815","title":"Fast-Slow Efficient Training for Multimodal Large Language Models via Visual Token Pruning","created":"2026-02-03","cited_by_count":0,"area":"mllm"},{"id":"2607.23913","title":"GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models","created":"2026-07-27","cited_by_count":0,"area":"mllm"},{"id":"2608.02134","title":"Messages, Not Tokens: Grounded Coresets for Faithful VLM Compression","created":"2026-08-03","cited_by_count":0,"area":"mllm"},{"id":"2609.16841","title":"StackTok: Accelerating VLMs Inference with Budget-Adaptive Visual Token Selection","created":"2026-09-15","cited_by_count":0,"area":"mllm"},{"id":"2609.34330","title":"MiCo: Mutual Information Coverage Optimization through Semantic Erasure Modeling for Efficient MLLM Inference","created":"2026-09-28","cited_by_count":0,"area":"mllm"}],"next_cursor":null}