{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:HWIUK3NBRPIHKK4SBTL7AAFC4S","short_pith_number":"pith:HWIUK3NB","schema_version":"1.0","canonical_sha256":"3d91456da18bd0752b920cd7f000a2e4bc9718538104e64e4aaa45ed88b86324","source":{"kind":"arxiv","id":"2201.12716","version":2},"attestation_state":"computed","paper":{"title":"You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Bowen Wen, Kostas Bekris, Stefan Schaal, Wenzhao Lian","submitted_at":"2022-01-30T03:59:14Z","abstract_excerpt":"Promising results have been achieved recently in category-level manipulation that generalizes across object instances. Nevertheless, it often requires expensive real-world data collection and manual specification of semantic keypoints for each object category and task. Additionally, coarse keypoint predictions and ignoring intermediate action sequences hinder adoption in complex manipulation tasks beyond pick-and-place. This work proposes a novel, category-level manipulation framework that leverages an object-centric, category-level representation and model-free 6 DoF motion tracking. The cano"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2201.12716","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2022-01-30T03:59:14Z","cross_cats_sorted":["cs.AI","cs.CV","cs.SY","eess.SY"],"title_canon_sha256":"3481e6f0fe74d35bfc4015146d90bdbe76aef5851a12a0011fc8f1efb949f1d5","abstract_canon_sha256":"e7a69a1a1607066d0df7bd110d19657e78a4166fa71556c95682117d29d0827a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:20:54.323646Z","signature_b64":"nuG04omGTqxCWhyxr/zrJ3yx13U61ODh2sju4wUacA7zeYkeH14D/+pSqUjx2mf2NoCaXpM+ZssVtqXf5j5ECw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3d91456da18bd0752b920cd7f000a2e4bc9718538104e64e4aaa45ed88b86324","last_reissued_at":"2026-07-05T04:20:54.323170Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:20:54.323170Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Bowen Wen, Kostas Bekris, Stefan Schaal, Wenzhao Lian","submitted_at":"2022-01-30T03:59:14Z","abstract_excerpt":"Promising results have been achieved recently in category-level manipulation that generalizes across object instances. Nevertheless, it often requires expensive real-world data collection and manual specification of semantic keypoints for each object category and task. Additionally, coarse keypoint predictions and ignoring intermediate action sequences hinder adoption in complex manipulation tasks beyond pick-and-place. This work proposes a novel, category-level manipulation framework that leverages an object-centric, category-level representation and model-free 6 DoF motion tracking. The cano"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.12716","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2201.12716/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2201.12716","created_at":"2026-07-05T04:20:54.323231+00:00"},{"alias_kind":"arxiv_version","alias_value":"2201.12716v2","created_at":"2026-07-05T04:20:54.323231+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.12716","created_at":"2026-07-05T04:20:54.323231+00:00"},{"alias_kind":"pith_short_12","alias_value":"HWIUK3NBRPIH","created_at":"2026-07-05T04:20:54.323231+00:00"},{"alias_kind":"pith_short_16","alias_value":"HWIUK3NBRPIHKK4S","created_at":"2026-07-05T04:20:54.323231+00:00"},{"alias_kind":"pith_short_8","alias_value":"HWIUK3NB","created_at":"2026-07-05T04:20:54.323231+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2607.01651","citing_title":"One Demonstration Is Enough for Real-World Robotic Reinforcement Learning","ref_index":27,"is_internal_anchor":false},{"citing_arxiv_id":"2604.15023","citing_title":"DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation","ref_index":28,"is_internal_anchor":false},{"citing_arxiv_id":"2604.16954","citing_title":"TSM-Pose: Topology-Aware Learning with Semantic Mamba for Category-Level Object Pose Estimation","ref_index":31,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S","json":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S.json","graph_json":"https://pith.science/api/pith-number/HWIUK3NBRPIHKK4SBTL7AAFC4S/graph.json","events_json":"https://pith.science/api/pith-number/HWIUK3NBRPIHKK4SBTL7AAFC4S/events.json","paper":"https://pith.science/paper/HWIUK3NB"},"agent_actions":{"view_html":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S","download_json":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S.json","view_paper":"https://pith.science/paper/HWIUK3NB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2201.12716&json=true","fetch_graph":"https://pith.science/api/pith-number/HWIUK3NBRPIHKK4SBTL7AAFC4S/graph.json","fetch_events":"https://pith.science/api/pith-number/HWIUK3NBRPIHKK4SBTL7AAFC4S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S/action/storage_attestation","attest_author":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S/action/author_attestation","sign_citation":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S/action/citation_signature","submit_replication":"https://pith.science/pith/HWIUK3NBRPIHKK4SBTL7AAFC4S/action/replication_record"}},"created_at":"2026-07-05T04:20:54.323231+00:00","updated_at":"2026-07-05T04:20:54.323231+00:00"}