{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UDQFSDY3HGCEKBDZJ6VBQLORIO","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9d381c2c8e4ae3f302802f93db3a3e697bed028455fe76a28e00a038135f717f","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-05-17T06:14:31Z","title_canon_sha256":"6d77f35d2953608a85426225257ef9c18a787e628a3d420e7c6a77bb6f826d7f"},"schema_version":"1.0","source":{"id":"2505.11865","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11865","created_at":"2026-07-05T11:04:53Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11865v1","created_at":"2026-07-05T11:04:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11865","created_at":"2026-07-05T11:04:53Z"},{"alias_kind":"pith_short_12","alias_value":"UDQFSDY3HGCE","created_at":"2026-07-05T11:04:53Z"},{"alias_kind":"pith_short_16","alias_value":"UDQFSDY3HGCEKBDZ","created_at":"2026-07-05T11:04:53Z"},{"alias_kind":"pith_short_8","alias_value":"UDQFSDY3","created_at":"2026-07-05T11:04:53Z"}],"graph_snapshots":[{"event_id":"sha256:727a693ac5799de5a5dab316f958310794e04c66883fb63c12eb6bdf72c30e5d","target":"graph","created_at":"2026-07-05T11:04:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2505.11865/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning manipulation skills from human demonstration videos offers a promising path toward generalizable and interpretable robotic intelligence-particularly through the lens of actionable affordances. However, transferring such knowledge remains challenging due to: 1) a lack of large-scale datasets with precise affordance annotations, and 2) insufficient exploration of affordances in diverse manipulation contexts. To address these gaps, we introduce HOVA-500K, a large-scale, affordance-annotated dataset comprising 500,000 images across 1,726 object categories and 675 actions. We also release ","authors_text":"Jiaming Zhou, Jia Zheng, Junwei Liang, Teli Ma, Zifan Wang, Ziyao Gao","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-05-17T06:14:31Z","title":"GLOVER++: Unleashing the Potential of Affordance Learning from Human Behaviors for Robotic Manipulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11865","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:94bebacb4e8463605f7bdc3af90deb32c67d457bd19bd486eaf84558982b0ce4","target":"record","created_at":"2026-07-05T11:04:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9d381c2c8e4ae3f302802f93db3a3e697bed028455fe76a28e00a038135f717f","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-05-17T06:14:31Z","title_canon_sha256":"6d77f35d2953608a85426225257ef9c18a787e628a3d420e7c6a77bb6f826d7f"},"schema_version":"1.0","source":{"id":"2505.11865","kind":"arxiv","version":1}},"canonical_sha256":"a0e0590f1b39844504794faa182dd143b01015e14d002078c8b301551d4843ef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0e0590f1b39844504794faa182dd143b01015e14d002078c8b301551d4843ef","first_computed_at":"2026-07-05T11:04:53.524501Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:04:53.524501Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WdaN5CzZUOPtv/n8Tiak48Eg4Y0MKQDaZHUb3D40+W5/MuffKxyk0P4ObS42aX0zVI/YLyMdRji+yPucec9kCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:04:53.525034Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.11865","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:94bebacb4e8463605f7bdc3af90deb32c67d457bd19bd486eaf84558982b0ce4","sha256:727a693ac5799de5a5dab316f958310794e04c66883fb63c12eb6bdf72c30e5d"],"state_sha256":"119603068284b45ad2a9c0b796388f3799cf0bd560ba059e1012fb2557e6e644"}