{"url":"/dataset/finecops-ref","name":"FineCops-Ref","full_name":null,"description_markdown":"FineCops-Ref is a dataset for Compositional Referring Expression Comprehension (REC) that rigorously evaluates Vision-Language Models (VLMs) on compositional reasoning and their ability to identify inconsistencies between images and text. Beyond standard REC tasks, it challenges models with fine-grained correspondences involving objects, attributes, and relationships. The dataset comprises both training and testing sets, designed to thoroughly assess model performance across various difficulty level.","description_withheld":null,"homepage":"https://arxiv.org/abs/2409.14750","introduced_date":"2024-09-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/finecops-ref-a-new-dataset-and-task-for-fine","title":"FineCops-Ref: A new Dataset and Task for Fine-Grained Compositional Referring Expression Comprehension","first_author":"Junzhuo Liu","url":null},"license":null,"modalities":[],"tasks":[{"name":"Referring Expression Comprehension","url":"/task/referring-expression-comprehension","datasets_with_task":"/datasets/task/referring-expression-comprehension"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["FineCops-Ref"],"data_loaders":[],"num_papers_in_archive":1,"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."}