Feed the Panel Dimensions, Not Verdicts: Rubric-Decomposed Fusion of Vision-Language Aesthetic Judges
cs.CV, cs.CL, cs.LG
Submitted: 2026-09-22
Updated: 2026-09-22
Code: https://github.com/chaofengc/IQA-PyTorch
Terminology
Sources
- Can Vision Language Models Assess Graphic Design Aesthetics? A Benchmark, Evaluation, and Dataset Perspective
- Multi-Granularity Reasoning for Image Quality Assessment via Attribute-Aware Reinforcement Learning to Rank
- AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception
- Are Diversity Metrics Measuring Diversity? A Capability-Controlled Audit of Majority-Vote Gain in LLM Ensembles
- Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panels
- Prometheus-Vision: Vision-Language Model as a Judge for Fine-Grained Evaluation
- DnA-Eval: Enhancing Large Language Model Evaluation through Decomposition and Aggregation
- Who Judges the Judge? LLM Jury-on-Demand: Building Trustworthy LLM Evaluation Systems
- Fusion-Eval: Integrating Assistant Evaluators with LLMs
- Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
- Mixture-of-Agents Enhances Large Language Model Capabilities
- UNIAA: A Unified Multi-modal Image Aesthetic Assessment Baseline and Benchmark
- AgenticIQA: An Agentic Framework for Adaptive and Interpretable Image Quality Assessment
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