{"total":25,"rows":[{"id":"2405.11273","title":"Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts","created":"2024-05-18","cited_by_count":108,"area":"mllm"},{"id":"2604.27393","title":"MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction","created":"2026-04-30","cited_by_count":78,"area":"mllm"},{"id":"2501.16566","title":"AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models","created":"2025-01-27","cited_by_count":44,"area":"mllm"},{"id":"2502.04424","title":"EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models","created":"2025-02-06","cited_by_count":32,"area":"mllm"},{"id":"2412.17759","title":"Survey of Large Multimodal Model Datasets, Application Categories and Taxonomy","created":"2024-12-23","cited_by_count":17,"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":"2412.17574","title":"HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks","created":"2024-12-23","cited_by_count":11,"area":"mllm"},{"id":"2404.00511","title":"MIPS at SemEval-2024 Task 3: Multimodal Emotion-Cause Pair Extraction in Conversations with Multimodal Language Models","created":"2024-03-31","cited_by_count":9,"area":"mllm"},{"id":"2606.15920","title":"OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing","created":"2026-06-14","cited_by_count":6,"area":"mllm"},{"id":"2505.20638","title":"Music Audio-Visual Question Answering Requires Specialized Multimodal Designs","created":"2025-05-27","cited_by_count":4,"area":"mllm"},{"id":"2505.24423","title":"MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs","created":"2025-05-30","cited_by_count":4,"area":"mllm"},{"id":"2412.08049","title":"EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion Understanding","created":"2024-12-11","cited_by_count":3,"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":"2601.22738","title":"StreamSense: Streaming Social Task Detection with Selective Vision-Language Model Routing","created":"2026-01-30","cited_by_count":2,"area":"mllm"},{"id":"2605.09996","title":"Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization","created":"2026-05-11","cited_by_count":1,"area":"mllm"},{"id":"2605.22109","title":"Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?","created":"2026-05-21","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"},{"id":"2509.02349","title":"AudioCodecBench: A Comprehensive Benchmark for Audio Codec Evaluation","created":"2025-09-02","cited_by_count":0,"area":"mllm"},{"id":"2509.19858","title":"Benchmarking Gaslighting Attacks Against Speech Large Language Models","created":"2025-09-24","cited_by_count":0,"area":"mllm"},{"id":"2512.04728","title":"Measuring the Unspoken: A Disentanglement Model and Benchmark for Psychological Analysis in the Wild","created":"2025-12-04","cited_by_count":0,"area":"mllm"},{"id":"2606.15694","title":"MAF: Multimodal Adaptive Few-shot Prompting for Sentiment Analysis with MLLMs","created":"2026-06-14","cited_by_count":0,"area":"mllm"},{"id":"2607.12787","title":"Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?","created":"2026-07-14","cited_by_count":0,"area":"mllm"},{"id":"2608.18132","title":"Alignment Is All You Need: Instruction-Free Training for General Audio-Language Models","created":"2026-07-28","cited_by_count":0,"area":"mllm"},{"id":"2610.00809","title":"Paying for Too Many Tokens? Valid and Cost-Efficient Multimodal LLM Annotation with Simple Heuristics","created":"2026-09-30","cited_by_count":0,"area":"mllm"},{"id":"2610.15129","title":"GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?","created":"2026-10-10","cited_by_count":0,"area":"mllm"}],"next_cursor":null}