{"url":"/dataset/monkey-v1-dataset","name":"Monkey V1 dataset","full_name":null,"description_markdown":"This dataset is used for neural co-training. \r\nmtl_monkey_dataset: was used for our MTL-Monkey model and involves neural responses that were predicted by a single-task trained model on real monkey V1.\r\nmtl_oracle_dataset: was used for our MTL-Oracle model and involves neural responses that were predicted by our image classification oracle.\r\nmtl_shuffled_dataset: was used for our MTL-Shuffled model and is the result of shuffling the mtl_monkey_dataset across images.","description_withheld":null,"homepage":"https://github.com/sinzlab/neural_cotraining","introduced_date":"2021-07-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/towards-robust-vision-by-multi-task-learning","title":"Towards robust vision by multi-task learning on monkey visual cortex","first_author":"Shahd Safarani","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Monkey V1 dataset"],"data_loaders":[{"repo":"https://github.com/sinzlab/neural_cotraining","url":"https://github.com/sinzlab/neural_cotraining","frameworks":[]}],"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."}