{"url":"/dataset/eqa","name":"EQA","full_name":"Embodied Question Answering","description_markdown":"The **EQA** (Embodied Question Answering) dataset is a dataset of visual questions and answers grounded in House3D. For this dataset an agent is spawned at a random location in a 3D environment and asked a question (for e.g. \"What color is the car?\"). In order to answer, the agent must first intelligently navigate to explore the environment, gather necessary visual information through first-person vision, and then answer the question (\"orange\").","description_withheld":null,"homepage":"https://embodiedqa.org/data","introduced_date":"2017-11-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/embodied-question-answering","title":"Embodied Question Answering","first_author":"Abhishek Das","url":null},"license":null,"modalities":[],"tasks":[{"name":"Embodied Question Answering","url":"/task/embodied-question-answering","datasets_with_task":"/datasets/task/embodied-question-answering"}],"languages":[],"variants":["EQA"],"data_loaders":[],"num_papers_in_archive":87,"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."}