{"url":"/dataset/office-home-lmt","name":"Office-Home-LMT","full_name":"Imbalance datasets for multi-domain adaptation","description_markdown":"The dataset is for research on the label distribution shift between multiple domain adaptations. We use **Cl**,  **Pr**, and **Rw** to resample two reverse long-tailed distributions and one Gaussian d for each of them for BTDA with label shift.","description_withheld":null,"homepage":"https://github.com/Pengchengpcx/Class-overwhelms-Mutual-Conditional-Blended-Target-Domain-Adaptation","introduced_date":"2023-02-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/class-overwhelms-mutual-conditional-blended","title":"Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation","first_author":"Pengcheng Xu","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Label shift of blended-target domain adaptation","url":"/task/label-shift-of-blended-target-domain","datasets_with_task":"/datasets/task/label-shift-of-blended-target-domain"}],"languages":[],"variants":["Office-Home-LMT"],"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."}