{"total":17,"rows":[{"id":"2204.14198","title":"Flamingo: a Visual Language Model for Few-Shot Learning","created":"2022-04-29","cited_by_count":4386,"area":"mllm"},{"id":"2404.05726","title":"MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding","created":"2024-04-08","cited_by_count":229,"area":"mllm"},{"id":"2210.09263","title":"Vision-Language Pre-training: Basics, Recent Advances, and Future Trends","created":"2022-10-17","cited_by_count":117,"area":"mllm"},{"id":"2505.04769","title":"Vision-Language-Action (VLA) Models: Concepts, Progress, Applications and Challenges","created":"2025-05-07","cited_by_count":74,"area":"mllm"},{"id":"2305.17718","title":"FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions","created":"2023-05-28","cited_by_count":33,"area":"mllm"},{"id":"2412.09754","title":"ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation","created":"2024-12-12","cited_by_count":17,"area":"mllm"},{"id":"2606.09393","title":"CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning","created":"2026-06-08","cited_by_count":8,"area":"mllm"},{"id":"2407.08150","title":"Hypergraph Multi-modal Large Language Model: Exploiting EEG and Eye-tracking Modalities to Evaluate Heterogeneous Responses for Video Understanding","created":"2024-07-11","cited_by_count":4,"area":"mllm"},{"id":"2211.16594","title":"Exploiting Category Names for Few-Shot Classification with Vision-Language Models","created":"2022-11-29","cited_by_count":3,"area":"mllm"},{"id":"2312.03936","title":"The Potential of Vision-Language Models for Content Moderation of Children's Videos","created":"2023-12-06","cited_by_count":2,"area":"mllm"},{"id":"2504.05491","title":"REEF: Relevance-Aware and Efficient LLM Adapter for Video Understanding","created":"2025-04-07","cited_by_count":2,"area":"mllm"},{"id":"2601.05495","title":"MMViR: A Multi-Modal and Multi-Granularity Representation for Long-range Video Understanding","created":"2026-01-09","cited_by_count":2,"area":"mllm"},{"id":"2305.02297","title":"Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime","created":"2023-05-03","cited_by_count":1,"area":"mllm"},{"id":"2505.24227","title":"Light as Deception: GPT-driven Natural Relighting Against Vision-Language Pre-training Models","created":"2025-05-30","cited_by_count":1,"area":"mllm"},{"id":"2511.15923","title":"RB-FT: Rationale-Bootstrapped Fine-Tuning for Video Classification","created":"2025-11-19","cited_by_count":1,"area":"mllm"},{"id":"2512.15957","title":"Seeing is Believing (and Predicting): Context-Aware Multi-Human Behavior Prediction with Vision Language Models","created":"2025-12-17","cited_by_count":1,"area":"mllm"},{"id":"2607.08489","title":"VEGAS: Human-Aligned Video Caption Evaluation via Gaze","created":"2026-07-09","cited_by_count":0,"area":"mllm"}],"next_cursor":null}