{"total":22,"rows":[{"id":"2405.17247","title":"An Introduction to Vision-Language Modeling","created":"2024-05-27","cited_by_count":178,"area":"mllm"},{"id":"2406.18915","title":"Manipulate-Anything: Automating Real-World Robots using Vision-Language Models","created":"2024-06-27","cited_by_count":83,"area":"mllm"},{"id":"2406.01837","title":"Boosting Vision-Language Models with Transduction","created":"2024-06-03","cited_by_count":36,"area":"mllm"},{"id":"2507.19024","title":"A Survey of Multimodal Hallucination Evaluation and Detection","created":"2025-07-25","cited_by_count":27,"area":"mllm"},{"id":"2407.08583","title":"The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective","created":"2024-07-11","cited_by_count":15,"area":"mllm"},{"id":"2409.12969","title":"Seeing Through Their Eyes: Evaluating Visual Perspective Taking in Vision Language Models","created":"2024-09-02","cited_by_count":15,"area":"mllm"},{"id":"2505.24693","title":"Conformal Prediction for Zero-Shot Models","created":"2025-05-30","cited_by_count":15,"area":"mllm"},{"id":"2410.01407","title":"AgriCLIP: Adapting CLIP for Agriculture and Livestock via Domain-Specialized Cross-Model Alignment","created":"2024-10-02","cited_by_count":13,"area":"mllm"},{"id":"2602.00135","title":"LLaVA-FA: Learning Fourier Approximation for Compressing Large Multimodal Models","created":"2026-01-28","cited_by_count":11,"area":"mllm"},{"id":"2502.09507","title":"When and How Does CLIP Enable Domain and Compositional Generalization?","created":"2025-02-13","cited_by_count":9,"area":"mllm"},{"id":"2506.06076","title":"Full Conformal Adaptation of Medical Vision-Language Models","created":"2025-06-06","cited_by_count":9,"area":"mllm"},{"id":"2506.17503","title":"Trustworthy Few-Shot Transfer of Medical VLMs through Split Conformal Prediction","created":"2025-06-20","cited_by_count":8,"area":"mllm"},{"id":"2506.17500","title":"Few-Shot, Now for Real: Medical VLMs Adaptation without Balanced Sets or Validation","created":"2025-06-20","cited_by_count":7,"area":"mllm"},{"id":"2510.03721","title":"Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models","created":"2025-10-04","cited_by_count":4,"area":"mllm"},{"id":"2505.15506","title":"Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts","created":"2025-05-21","cited_by_count":3,"area":"mllm"},{"id":"2406.12321","title":"Automatic benchmarking of large multimodal models via iterative experiment programming","created":"2024-06-18","cited_by_count":2,"area":"mllm"},{"id":"2407.05061","title":"Test-time Contrastive Concepts for Open-world Semantic Segmentation with Vision-Language Models","created":"2024-07-06","cited_by_count":2,"area":"mllm"},{"id":"2505.03374","title":"Reducing Annotation Burden in Physical Activity Research Using Vision-Language Models","created":"2025-05-06","cited_by_count":0,"area":"mllm"},{"id":"2507.08000","title":"Impact of Pretraining Word Co-occurrence on Compositional Generalization in Multimodal Models","created":"2025-07-10","cited_by_count":0,"area":"mllm"},{"id":"2603.02959","title":"Semi-Supervised Few-Shot Adaptation of Vision-Language Models","created":"2026-03-03","cited_by_count":0,"area":"mllm"},{"id":"2603.04346","title":"Underrepresented in Foundation Model Pretraining Data? A One-Shot Probe","created":"2026-03-04","cited_by_count":0,"area":"mllm"},{"id":"2604.27932","title":"Dynamic Cluster Data Sampling for Efficient and Long-Tail-Aware Vision-Language Pre-training","created":"2026-04-30","cited_by_count":0,"area":"mllm"}],"next_cursor":null}