{"url":"/dataset/causalchaos","name":"CausalChaos!","full_name":"CausalChaos!QA","description_markdown":"CausalChaos! is a dataset for causal video question answering. It is based on Tom and Jerry cartoons. It features longer causal chains embedded in dynamic visual scenes. It also features challenging incorrect options, especially, Causal Confusion set which contains causally confounding incorrect options. All these factors prove to be challenging for current VLMs and other traditional Video Question Answering models.","description_withheld":null,"homepage":"https://github.com/LUNAProject22/CausalChaos","introduced_date":"2024-04-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/causalchaos-dataset-for-comprehensive-causal","title":"CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes","first_author":"Paritosh Parmar","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"}],"tasks":[{"name":"Visual Question Answering (VQA)","url":"/task/visual-question-answering","datasets_with_task":"/datasets/task/visual-question-answering"},{"name":"Video Question Answering","url":"/task/video-question-answering","datasets_with_task":"/datasets/task/video-question-answering"},{"name":"Zeroshot Video Question Answer","url":"/task/zeroshot-video-question-answer-1","datasets_with_task":"/datasets/task/zeroshot-video-question-answer-1"},{"name":"Causal Discovery in Video Reasoning","url":"/task/causal-discovery-in-video-reasoning","datasets_with_task":"/datasets/task/causal-discovery-in-video-reasoning"},{"name":"Causal Discovery","url":"/task/causal-discovery","datasets_with_task":"/datasets/task/causal-discovery"},{"name":"Commonsense Causal Reasoning","url":"/task/commonsense-causal-reasoning","datasets_with_task":"/datasets/task/commonsense-causal-reasoning"},{"name":"Few-shot Video Question Answering","url":"/task/few-shot-video-question-answering","datasets_with_task":"/datasets/task/few-shot-video-question-answering"},{"name":"Grounded Video Question Answering","url":"/task/grounded-video-question-answering","datasets_with_task":"/datasets/task/grounded-video-question-answering"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["CausalChaos!"],"data_loaders":[{"repo":"https://github.com/lunaproject22/causalchaos","url":"https://github.com/LUNAProject22/CausalChaos","frameworks":["tf","pytorch","jax"]}],"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."}