{"url":"/dataset/refomb","name":"RefoMB","full_name":null,"description_markdown":"The **RefoMB dataset** is part of a project called **RLAIF-V**, which stands for \"Aligning MLLMs through Open-Source AI Feedback for Super GPT-4V Trustworthiness.\" It's an open-source multimodal preference dataset that contains more than **30,000 high-quality comparison pairs**. The dataset is designed to reduce hallucination in different Multimodal Large Language Models (MLLMs) and improve their trustworthiness by providing high-quality feedback data and an online feedback learning algorithm.\r\n\r\nThe **RefoMB** itself is a comprehensive multimodal evaluation set that covers **8 sub-abilities** of multimodal model perception and reasoning. It includes a variety of image types such as cartoons, text-rich images, and photos to assess the credibility of responses and general performance of current multimodal models in open-ended generation tasks.","description_withheld":null,"homepage":"https://github.com/RLHF-V/RLAIF-V","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["RefoMB"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}