{"total":54,"rows":[{"id":"2109.01134","title":"Learning to Prompt for Vision-Language Models","created":"2021-09-02","cited_by_count":2281,"area":"mllm"},{"id":"2203.05557","title":"Conditional Prompt Learning for Vision-Language Models","created":"2022-03-10","cited_by_count":1433,"area":"mllm"},{"id":"2210.07183","title":"Visual Classification via Description from Large Language Models","created":"2022-10-13","cited_by_count":336,"area":"mllm"},{"id":"2303.13283","title":"Visual-Language Prompt Tuning with Knowledge-guided Context Optimization","created":"2023-03-23","cited_by_count":308,"area":"mllm"},{"id":"2205.03340","title":"Prompt Distribution Learning","created":"2022-05-06","cited_by_count":235,"area":"mllm"},{"id":"2109.11797","title":"CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Models","created":"2021-09-24","cited_by_count":183,"area":"mllm"},{"id":"2402.17766","title":"ShapeLLM: Universal 3D Object Understanding for Embodied Interaction","created":"2024-02-27","cited_by_count":137,"area":"mllm"},{"id":"2209.15517","title":"Medical Image Understanding with Pretrained Vision Language Models: A Comprehensive Study","created":"2022-09-30","cited_by_count":66,"area":"mllm"},{"id":"2210.01253","title":"PLOT: Prompt Learning with Optimal Transport for Vision-Language Models","created":"2022-10-03","cited_by_count":64,"area":"mllm"},{"id":"2111.14745","title":"A Simple Long-Tailed Recognition Baseline via Vision-Language Model","created":"2021-11-29","cited_by_count":49,"area":"mllm"},{"id":"2309.03406","title":"Distribution-Aware Prompt Tuning for Vision-Language Models","created":"2023-09-06","cited_by_count":35,"area":"mllm"},{"id":"2205.11169","title":"PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models","created":"2022-05-23","cited_by_count":30,"area":"mllm"},{"id":"2304.05995","title":"APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIP","created":"2023-04-12","cited_by_count":24,"area":"mllm"},{"id":"2303.06571","title":"Gradient-Regulated Meta-Prompt Learning for Generalizable Vision-Language Models","created":"2023-03-12","cited_by_count":21,"area":"mllm"},{"id":"2403.16442","title":"If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions","created":"2024-03-25","cited_by_count":14,"area":"mllm"},{"id":"2406.00345","title":"DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection","created":"2024-06-01","cited_by_count":14,"area":"mllm"},{"id":"2311.07593","title":"Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification","created":"2023-11-10","cited_by_count":13,"area":"mllm"},{"id":"2210.10841","title":"Prompting through Prototype: A Prototype-based Prompt Learning on Pretrained Vision-Language Models","created":"2022-10-19","cited_by_count":12,"area":"mllm"},{"id":"2403.00219","title":"Multi-modal Attribute Prompting for Vision-Language Models","created":"2024-03-01","cited_by_count":12,"area":"mllm"},{"id":"2504.05457","title":"Taxonomy-Aware Evaluation of Vision-Language Models","created":"2025-04-07","cited_by_count":11,"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":"2307.00910","title":"CoPL: Contextual Prompt Learning for Vision-Language Understanding","created":"2023-07-03","cited_by_count":10,"area":"mllm"},{"id":"2308.01126","title":"Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training Model","created":"2023-08-02","cited_by_count":10,"area":"mllm"},{"id":"2402.03783","title":"Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning","created":"2024-02-06","cited_by_count":10,"area":"mllm"},{"id":"2409.19806","title":"PALM: Few-Shot Prompt Learning for Audio Language Models","created":"2024-09-29","cited_by_count":8,"area":"mllm"},{"id":"2112.05587","title":"Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation","created":"2021-12-10","cited_by_count":7,"area":"mllm"},{"id":"2211.16504","title":"Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles","created":"2022-11-29","cited_by_count":7,"area":"mllm"},{"id":"2410.04819","title":"MINER: Mining the Underlying Pattern of Modality-Specific Neurons in Multimodal Large Language Models","created":"2024-10-07","cited_by_count":7,"area":"mllm"},{"id":"2311.15812","title":"C-SAW: Self-Supervised Prompt Learning for Image Generalization in Remote Sensing","created":"2023-11-27","cited_by_count":6,"area":"mllm"},{"id":"2309.01479","title":"Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models","created":"2023-09-04","cited_by_count":5,"area":"mllm"},{"id":"2405.00693","title":"Leveraging Large Language Models in Human-Robot Interaction: A Critical Analysis of Potential and Pitfalls","created":"2024-03-26","cited_by_count":5,"area":"mllm"},{"id":"2306.15706","title":"Approximated Prompt Tuning for Vision-Language Pre-trained Models","created":"2023-06-27","cited_by_count":4,"area":"mllm"},{"id":"2506.16396","title":"GoalLadder: Incremental Goal Discovery with Vision-Language Models","created":"2025-06-19","cited_by_count":3,"area":"mllm"},{"id":"2507.07048","title":"Comprehensive Evaluation of Large Multimodal Models for Nutrition Analysis: A New Benchmark Enriched with Contextual Metadata","created":"2025-07-09","cited_by_count":3,"area":"mllm"},{"id":"2508.18297","title":"Can VLMs Recall Factual Associations From Visual References?","created":"2025-08-22","cited_by_count":3,"area":"mllm"},{"id":"2509.08461","title":"Adapting Vision-Language Models for Neutrino Event Classification in High-Energy Physics","created":"2025-09-10","cited_by_count":3,"area":"mllm"},{"id":"2503.01531","title":"Diversity Covariance-Aware Prompt Learning for Vision-Language Models","created":"2025-03-03","cited_by_count":2,"area":"mllm"},{"id":"2504.16433","title":"FrogDogNet: Fourier frequency Retained visual prompt Output Guidance for Domain Generalization of CLIP in Remote Sensing","created":"2025-04-23","cited_by_count":2,"area":"mllm"},{"id":"2511.00191","title":"A Retrospect to Multi-prompt Learning across Vision and Language","created":"2025-10-31","cited_by_count":2,"area":"mllm"},{"id":"2310.09767","title":"VLIS: Unimodal Language Models Guide Multimodal Language Generation","created":"2023-10-15","cited_by_count":1,"area":"mllm"},{"id":"2404.11864","title":"Progressive Multi-modal Conditional Prompt Tuning","created":"2024-04-18","cited_by_count":1,"area":"mllm"},{"id":"2411.02074","title":"GraphVL: Graph-Enhanced Semantic Modeling via Vision-Language Models for Generalized Class Discovery","created":"2024-11-04","cited_by_count":1,"area":"mllm"},{"id":"2412.10680","title":"UCDR-Adapter: Exploring Adaptation of Pre-Trained Vision-Language Models for Universal Cross-Domain Retrieval","created":"2024-12-14","cited_by_count":1,"area":"mllm"},{"id":"2508.04942","title":"Accelerating Conditional Prompt Learning via Masked Image Modeling for Vision-Language Models","created":"2025-08-07","cited_by_count":1,"area":"mllm"},{"id":"2302.01582","title":"Controlling for Stereotypes in Multimodal Language Model Evaluation","created":"2023-02-03","cited_by_count":0,"area":"mllm"},{"id":"2305.06221","title":"Multi-Prompt with Depth Partitioned Cross-Modal Learning","created":"2023-05-10","cited_by_count":0,"area":"mllm"},{"id":"2309.07760","title":"PRE: Vision-Language Prompt Learning with Reparameterization Encoder","created":"2023-09-14","cited_by_count":0,"area":"mllm"},{"id":"2408.11761","title":"D-RMGPT: Robot-assisted collaborative tasks driven by large multimodal models","created":"2024-08-21","cited_by_count":0,"area":"mllm"},{"id":"2507.07147","title":"Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation","created":"2025-07-09","cited_by_count":0,"area":"mllm"},{"id":"2510.19316","title":"KORE: Enhancing Knowledge Injection for Large Multimodal Models via Knowledge-Oriented Controls","created":"2025-10-22","cited_by_count":0,"area":"mllm"},{"id":"2603.08347","title":"Local-Global Prompt Learning via Sparse Optimal Transport","created":"2026-03-09","cited_by_count":0,"area":"mllm"},{"id":"2607.18615","title":"Stochastic Meta-Unlearning: Bridging Language Backbone and Multimodal Unlearning","created":"2026-07-21","cited_by_count":0,"area":"mllm"},{"id":"2608.27225","title":"STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration","created":"2026-08-27","cited_by_count":0,"area":"mllm"},{"id":"2610.19407","title":"Vision-Language Models Integrate Conflicting Evidence Like Biased Bayesian Observers","created":"2026-10-14","cited_by_count":0,"area":"mllm"}],"next_cursor":null}