{"total":25,"rows":[{"id":"2501.11561","title":"Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution","created":"2025-01-20","cited_by_count":141,"area":"mllm"},{"id":"2405.19298","title":"Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare","created":"2024-05-29","cited_by_count":66,"area":"mllm"},{"id":"2401.08276","title":"AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception","created":"2024-01-16","cited_by_count":65,"area":"mllm"},{"id":"2403.10854","title":"A Comprehensive Study of Multimodal Large Language Models for Image Quality Assessment","created":"2024-03-16","cited_by_count":43,"area":"mllm"},{"id":"2404.13306","title":"FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models","created":"2024-04-20","cited_by_count":36,"area":"mllm"},{"id":"2410.05474","title":"R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?","created":"2024-10-07","cited_by_count":30,"area":"mllm"},{"id":"2411.17221","title":"AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMM","created":"2024-11-26","cited_by_count":24,"area":"mllm"},{"id":"2402.18068","title":"SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language Model","created":"2024-02-28","cited_by_count":15,"area":"mllm"},{"id":"2403.12806","title":"VisualCritic: Making LMMs Perceive Visual Quality Like Humans","created":"2024-03-19","cited_by_count":13,"area":"mllm"},{"id":"2406.01069","title":"UniQA: Unified Vision-Language Pre-training for Image Quality and Aesthetic Assessment","created":"2024-06-03","cited_by_count":13,"area":"mllm"},{"id":"2411.17237","title":"Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessment","created":"2024-11-26","cited_by_count":12,"area":"mllm"},{"id":"2509.25787","title":"Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking","created":"2025-09-30","cited_by_count":10,"area":"mllm"},{"id":"2503.10079","title":"Information Density Principle for MLLM Benchmarks","created":"2025-03-13","cited_by_count":9,"area":"mllm"},{"id":"2503.02206","title":"Language-Guided Visual Perception Disentanglement for Image Quality Assessment and Conditional Image Generation","created":"2025-03-04","cited_by_count":5,"area":"mllm"},{"id":"2409.05381","title":"Few-Shot Image Quality Assessment via Adaptation of Vision-Language Models","created":"2024-09-09","cited_by_count":4,"area":"mllm"},{"id":"2606.16799","title":"Decoupling Semantics from Distortions: Multi-Scale Two-Stream Vision-Language Alignment for AI-Generated Image Quality Assessment","created":"2026-06-15","cited_by_count":4,"area":"mllm"},{"id":"2412.06760","title":"Ranking-aware adapter for text-driven image ordering with CLIP","created":"2024-12-09","cited_by_count":2,"area":"mllm"},{"id":"2412.10594","title":"Towards Unified Benchmark and Models for Multi-Modal Perceptual Metrics","created":"2024-12-13","cited_by_count":2,"area":"mllm"},{"id":"2503.20673","title":"Mitigating Low-Level Visual Hallucinations Requires Self-Awareness: Database, Model and Training Strategy","created":"2025-03-26","cited_by_count":1,"area":"mllm"},{"id":"2511.17962","title":"VITAL: Vision-Encoder-centered Pre-training for LMMs in Visual Quality Assessment","created":"2025-11-22","cited_by_count":1,"area":"mllm"},{"id":"2601.15356","title":"Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing","created":"2026-01-21","cited_by_count":1,"area":"mllm"},{"id":"2601.20689","title":"Decoupling Perception and Calibration: Label-Efficient Image Quality Assessment Framework","created":"2026-01-28","cited_by_count":1,"area":"mllm"},{"id":"2507.14997","title":"Language Integration in Fine-Tuning Multimodal Large Language Models for Image-Based Regression","created":"2025-07-20","cited_by_count":0,"area":"mllm"},{"id":"2603.14951","title":"GT-PCQA: Geometry-Texture Decoupled Point Cloud Quality Assessment with MLLM","created":"2026-03-16","cited_by_count":0,"area":"mllm"},{"id":"2609.37576","title":"Evaluating the Evaluators: Diagnosing Large Multimodal Models for AI-Generated Image Assessment","created":"2026-09-29","cited_by_count":0,"area":"mllm"}],"next_cursor":null}