{"total":13,"rows":[{"id":"2503.12769","title":"ViSpeak: Visual Instruction Feedback in Streaming Videos","created":"2025-03-17","cited_by_count":42,"area":"mllm"},{"id":"2506.21862","title":"LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs","created":"2025-06-27","cited_by_count":26,"area":"mllm"},{"id":"2508.09210","title":"MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models","created":"2025-08-11","cited_by_count":17,"area":"mllm"},{"id":"2507.10300","title":"FaceLLM: A Multimodal Large Language Model for Face Understanding","created":"2025-07-14","cited_by_count":15,"area":"mllm"},{"id":"2504.18152","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","created":"2025-04-25","cited_by_count":7,"area":"mllm"},{"id":"2511.18823","title":"VideoPerceiver: Enhancing Fine-Grained Temporal Perception in Video Multimodal Large Language Models","created":"2025-11-24","cited_by_count":5,"area":"mllm"},{"id":"2508.02429","title":"Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting","created":"2025-08-04","cited_by_count":3,"area":"mllm"},{"id":"2606.24286","title":"AVOC: Enhancing Hour-Level Audio-Video Understanding in Omni-Modal LLMs via Retrieval-Inspired Token Compression","created":"2026-06-23","cited_by_count":3,"area":"mllm"},{"id":"2508.10016","title":"Training-Free Multimodal Large Language Model Orchestration","created":"2025-08-06","cited_by_count":2,"area":"mllm"},{"id":"2511.12077","title":"Learning to Hear by Seeing: It's Time for Vision Language Models to Understand Artistic Emotion from Sight and Sound","created":"2025-11-15","cited_by_count":1,"area":"mllm"},{"id":"2603.18480","title":"Do Vision Language Models Understand Human Engagement in Games?","created":"2026-03-19","cited_by_count":1,"area":"mllm"},{"id":"2606.07643","title":"AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs","created":"2026-06-01","cited_by_count":1,"area":"mllm"},{"id":"2608.10796","title":"E$^3$mo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment","created":"2026-08-11","cited_by_count":1,"area":"mllm"}],"next_cursor":null}