{"url":"/dataset/e-vqa","name":"E-VQA","full_name":null,"description_markdown":"This dataset, adapted from VQAv2, is designed for the *Visual Question Answering* task  and evaluates multimodal model editing in terms of reliability, stability and generality. You can download the dataset from [here](https://drive.google.com/drive/folders/1jBdTJxUb9wEeHnvG-RY8dv5_I4QlDpUS?usp=drive_link)","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["E-VQA"],"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."}