{"total":18,"rows":[{"id":"2405.16148","title":"Accelerating Transformers with Spectrum-Preserving Token Merging","created":"2024-05-25","cited_by_count":35,"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":"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":"2602.08005","title":"ResidualKV: Residual-Based KV Cache Compression for Efficient Long-Context Inference","created":"2026-02-08","cited_by_count":9,"area":"inference"},{"id":"2412.09919","title":"B-VLLM: A Vision Large Language Model with Balanced Spatio-Temporal Tokens","created":"2024-12-13","cited_by_count":6,"area":"inference"},{"id":"2502.06474","title":"UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths","created":"2025-02-10","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":"2512.14661","title":"Focus: A Streaming Concentration Architecture for Efficient Vision-Language Models","created":"2025-12-16","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":"2605.12309","title":"G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models","created":"2026-05-12","cited_by_count":3,"area":"inference"},{"id":"2605.08029","title":"STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation","created":"2026-05-08","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":"2603.27900","title":"R\\'enyi Entropy: A New Token Pruning Metric for Vision Transformers","created":"2026-03-29","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":"2608.29291","title":"Accelerating Unified Multimodal Models with Core-Expansion Routing and Unified Computation Scheduling","created":"2026-08-29","cited_by_count":0,"area":"inference"},{"id":"2609.32831","title":"UniCache: Task- and Type-Aware KV Cache Compression for Unified Multimodal Models","created":"2026-09-26","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"}],"next_cursor":null}