The study evaluates whether multimodal large language models (MLLMs) can produce open‑ended aesthetic critiques comparable to humans. Eight open‑weight MLLMs (7 B–397 B) and GPT‑5.5 were tested on 1,227 r/photocritique posts under various prompts, revealing that reference‑based similarity metrics often misrepresent model performance, while shorter critiques and image‑omission had limited impact. Human judges and annotators found the models’ critiques largely different from human ones, noting that models tend to be overly comprehensive and repetitive rather than selective and specific.
By Sajjad Ghiasvand, Maryam Amirizaniani, Haniyeh Ehsani Oskouie, Mahnoosh Alizadeh, Ramtin Pedarsani
arXiv:2607. 04147v1 Announce Type: cross Abstract: Automated fine-grained perception of calligraphy styles--a task vital to cultural heritage preservation--remains a critical challenge for Large Vision-Language Models (LVLMs), largely constrained by existing datasets that suffer from modal mixture and flattened labels.
By Yinsheng Yao, Yan Liu, Chen Ye
The paper introduces VMetaphor-Bench, a benchmark for evaluating visual metaphor generation in text-to-image models, comprising 1,500 curated metaphors across three levels and ten categories, each paired with two prompts of varying specificity. It proposes a hybrid evaluation framework using a multiple-choice question protocol and dimension-based scoring to assess metaphorical fidelity. Experiments on 11 T2I models show that even top proprietary models struggle with compositional structuring and cross-domain mapping, underscoring the need for further research in this area.
By Chuer Chen, Zichen Wang, Yi He, Zhengxi Yu, Nan Cao
The paper introduces VMetaphor-Bench, a benchmark for assessing visual metaphor generation in text-to-image models. It contains 1,500 curated metaphors across three levels and ten categories, each paired with two prompts of varying specificity. The authors evaluate 11 T2I models using a hybrid MLLM-as-judge framework that combines a large multiple-choice question set with dimension-based scoring, finding that even top proprietary models struggle with compositional structuring and cross-domain mapping.
Traditional Image Aesthetic Assessment (IAA) methods mainly rely on regressing absolute Mean Opinion Scores (MOS). However, such a paradigm overlooks the inherently dynamic nature of human aesthetic perception, which relies on subconscious comparison against implicit visual references.
arXiv:2606. 30026v1 Announce Type: cross Abstract: Audiovisual arts encompass diverse creative disciplines, including cinema, visual arts, stage performance, and game design, where artistic meaning arises from deliberate combinations of visual, auditory, and narrative elements (e.
By Yuxuan Fan, Gyusik Seo, Jing Hao, Jaemin Cho, Mohit Bansal, Jaehong Yoon