datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multimodal-LLMs-See-Sentiment
MLLMsent — datasets and experiment results
Every input and every output of "Multimodal LLMs See Sentiment"
(arXiv:2508.16873): the image descriptions generated by six multimodal
LLMs, the sentiment labels derived from the PerceptSent annotations, and the complete
per-fold results of all 141 experiments.
Paper: arXiv:2508.16873
Code, training and inference: https://github.com/neemiasbsilva/multimodal-LLMs-see-sentiment
Model checkpoints:… See the full description on the dataset page: https://huggingface.co/datasets/neemiasbsilva/multimodal-LLMs-See-Sentiment.ad-creative-quality-human-vs-llm
Human Expert vs LLM Judge: Facebook Ad Creative Quality
500 real Facebook ads from 253 advertisers, each rated for creative quality by a human ad expert AND by a vision LLM — with the LLM's full reasoning.
The headline finding baked into this data: the human and the LLM agree on image quality only 26.8% of the time. The LLM judge rates 71.8% of ads "good"; the human expert rates only 20% "good". If you are using an LLM as a judge of ad creative (or any subjective visual quality)… See the full description on the dataset page: https://huggingface.co/datasets/AdControlCenter/ad-creative-quality-human-vs-llm.