{"url":"/task/3d-parameter-efficient-fine-tuning-for","name":"3D Parameter-Efficient Fine-Tuning for Classification","slug":"3d-parameter-efficient-fine-tuning-for","description_markdown":null,"categories":[],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":4,"papers_with_code":4,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":2,"subtasks":0,"parent_tasks":0},"benchmarks":[],"datasets":[{"url":"/dataset/modelnet","name":"ModelNet","full_name":"","num_papers_in_archive":1406},{"url":"/dataset/scanobjectnn","name":"ScanObjectNN","full_name":"","num_papers_in_archive":337}],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":4,"of":4,"tagged_in_all":4,"items":[{"url":"/paper/instance-aware-dynamic-prompt-tuning-for-pre","title":"Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models","date":"2023-04-14","arxiv_id":"2304.07221","repositories_listed":3,"syntology":{"n":14,"n_ran":9,"n_unverified":5,"n_pointer_only":14}},{"url":"/paper/parameter-efficient-fine-tuning-in-spectral","title":"Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning","date":"2024-10-10","arxiv_id":"2410.08114","repositories_listed":1,"syntology":{"n":13,"n_ran":12,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/positional-prompt-tuning-for-efficient-3d","title":"Positional Prompt Tuning for Efficient 3D Representation Learning","date":"2024-08-21","arxiv_id":"2408.11567","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-adapter-meets-prompt-tuning-parameter","title":"Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis","date":"2024-03-03","arxiv_id":"2403.01439","repositories_listed":1,"syntology":{"n":7,"n_ran":4,"n_unverified":3,"n_pointer_only":0}}],"syntology_records":3,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}