{"total":23,"rows":[{"id":"2111.03930","title":"Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling","created":"2021-11-06","cited_by_count":431,"area":"mllm"},{"id":"2207.09519","title":"Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification","created":"2022-07-19","cited_by_count":362,"area":"mllm"},{"id":"2403.18293","title":"Efficient Test-Time Adaptation of Vision-Language Models","created":"2024-03-27","cited_by_count":141,"area":"mllm"},{"id":"2503.02199","title":"Words or Vision: Do Vision-Language Models Have Blind Faith in Text?","created":"2025-03-04","cited_by_count":89,"area":"mllm"},{"id":"2404.14047","title":"An empirical study of LLaMA3 quantization: from LLMs to MLLMs","created":"2024-04-22","cited_by_count":64,"area":"mllm"},{"id":"2410.07177","title":"MM-Ego: Towards Building Egocentric Multimodal LLMs for Video QA","created":"2024-10-09","cited_by_count":24,"area":"mllm"},{"id":"2310.02998","title":"ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models","created":"2023-10-04","cited_by_count":19,"area":"mllm"},{"id":"2408.03735","title":"Advancing Multimodal Large Language Models with Quantization-Aware Scale Learning for Efficient Adaptation","created":"2024-08-07","cited_by_count":15,"area":"mllm"},{"id":"2306.08685","title":"World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Language Models","created":"2023-06-14","cited_by_count":10,"area":"mllm"},{"id":"2505.14071","title":"Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models","created":"2025-05-20","cited_by_count":9,"area":"mllm"},{"id":"2508.03351","title":"SalQ-VLM: Fine-Grained Saliency-Guided Quantization for Vision-Language Models","created":"2025-08-05","cited_by_count":8,"area":"mllm"},{"id":"2505.18413","title":"LatentLLM: Attention-Aware Joint Tensor Compression","created":"2025-05-23","cited_by_count":7,"area":"mllm"},{"id":"2503.05936","title":"CASP: Compression of Large Multimodal Models Based on Attention Sparsity","created":"2025-03-07","cited_by_count":5,"area":"mllm"},{"id":"2510.05544","title":"Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM","created":"2025-10-07","cited_by_count":3,"area":"mllm"},{"id":"2311.07449","title":"Semantically Grounded QFormer for Efficient Vision Language Understanding","created":"2023-11-13","cited_by_count":2,"area":"mllm"},{"id":"2505.21465","title":"ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models","created":"2025-05-27","cited_by_count":2,"area":"mllm"},{"id":"2606.03093","title":"Decomposing how prompting steers behavior","created":"2026-06-02","cited_by_count":2,"area":"mllm"},{"id":"2604.17320","title":"Towards Joint Quantization and Token Pruning of Vision-Language Models","created":"2026-04-19","cited_by_count":1,"area":"mllm"},{"id":"2605.05910","title":"Plug-and-play Class-aware Knowledge Injection for Prompt Learning with Visual-Language Model","created":"2026-05-07","cited_by_count":1,"area":"mllm"},{"id":"2309.14928","title":"Noise-Tolerant Few-Shot Unsupervised Adapter for Vision-Language Models","created":"2023-09-26","cited_by_count":0,"area":"mllm"},{"id":"2608.19208","title":"When Irrelevant Text Matters: Affine Margin Shifts in Multimodal Large Language Models","created":"2026-06-12","cited_by_count":0,"area":"mllm"},{"id":"2608.26641","title":"Information-Guided Frontier Decoding: Contextual Utility-Driven Commitment in dMLLMs","created":"2026-08-27","cited_by_count":0,"area":"mllm"},{"id":"2609.32489","title":"When Helpful Text Hurts: Option-Redirecting Bias in Vision-Language Models","created":"2026-09-26","cited_by_count":0,"area":"mllm"}],"next_cursor":null}