{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:YPRDWGF52MHIZZJWIDEHPWND7K","short_pith_number":"pith:YPRDWGF5","schema_version":"1.0","canonical_sha256":"c3e23b18bdd30e8ce53640c877d9a3fa8303d2d14cdf91173db164b0caed03f2","source":{"kind":"arxiv","id":"2508.12948","version":1},"attestation_state":"computed","paper":{"title":"MaskSem: Semantic-Guided Masking for Learning 3D Hybrid High-Order Motion Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianqin Yin, Shaojie Zhang, Wei Wei, Yonghao Dang","submitted_at":"2025-08-18T14:24:04Z","abstract_excerpt":"Human action recognition is a crucial task for intelligent robotics, particularly within the context of human-robot collaboration research. In self-supervised skeleton-based action recognition, the mask-based reconstruction paradigm learns the spatial structure and motion patterns of the skeleton by masking joints and reconstructing the target from unlabeled data. However, existing methods focus on a limited set of joints and low-order motion patterns, limiting the model's ability to understand complex motion patterns. To address this issue, we introduce MaskSem, a novel semantic-guided maskin"},"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":"2508.12948","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-18T14:24:04Z","cross_cats_sorted":[],"title_canon_sha256":"417e89c395c4837ffb5109c8e035f050f691eb3b62060174807bffb2778e3d02","abstract_canon_sha256":"30073dcd5eb688dc0472931c896ca3e1fb8f54b194afd964798d38ed086f9144"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:55:29.763499Z","signature_b64":"4ZSz+ymwc/RFUryj9PQNSxI8GQoxSvFe+0040NhOVyLZ7JLVNSkWWtC48m760RVvpftSCRKvtRRzgT2REgGcBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3e23b18bdd30e8ce53640c877d9a3fa8303d2d14cdf91173db164b0caed03f2","last_reissued_at":"2026-07-05T11:55:29.763012Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:55:29.763012Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MaskSem: Semantic-Guided Masking for Learning 3D Hybrid High-Order Motion Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianqin Yin, Shaojie Zhang, Wei Wei, Yonghao Dang","submitted_at":"2025-08-18T14:24:04Z","abstract_excerpt":"Human action recognition is a crucial task for intelligent robotics, particularly within the context of human-robot collaboration research. In self-supervised skeleton-based action recognition, the mask-based reconstruction paradigm learns the spatial structure and motion patterns of the skeleton by masking joints and reconstructing the target from unlabeled data. However, existing methods focus on a limited set of joints and low-order motion patterns, limiting the model's ability to understand complex motion patterns. To address this issue, we introduce MaskSem, a novel semantic-guided maskin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.12948","kind":"arxiv","version":1},"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/2508.12948/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":"2508.12948","created_at":"2026-07-05T11:55:29.763067+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.12948v1","created_at":"2026-07-05T11:55:29.763067+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.12948","created_at":"2026-07-05T11:55:29.763067+00:00"},{"alias_kind":"pith_short_12","alias_value":"YPRDWGF52MHI","created_at":"2026-07-05T11:55:29.763067+00:00"},{"alias_kind":"pith_short_16","alias_value":"YPRDWGF52MHIZZJW","created_at":"2026-07-05T11:55:29.763067+00:00"},{"alias_kind":"pith_short_8","alias_value":"YPRDWGF5","created_at":"2026-07-05T11:55:29.763067+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K","json":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K.json","graph_json":"https://pith.science/api/pith-number/YPRDWGF52MHIZZJWIDEHPWND7K/graph.json","events_json":"https://pith.science/api/pith-number/YPRDWGF52MHIZZJWIDEHPWND7K/events.json","paper":"https://pith.science/paper/YPRDWGF5"},"agent_actions":{"view_html":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K","download_json":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K.json","view_paper":"https://pith.science/paper/YPRDWGF5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.12948&json=true","fetch_graph":"https://pith.science/api/pith-number/YPRDWGF52MHIZZJWIDEHPWND7K/graph.json","fetch_events":"https://pith.science/api/pith-number/YPRDWGF52MHIZZJWIDEHPWND7K/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K/action/storage_attestation","attest_author":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K/action/author_attestation","sign_citation":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K/action/citation_signature","submit_replication":"https://pith.science/pith/YPRDWGF52MHIZZJWIDEHPWND7K/action/replication_record"}},"created_at":"2026-07-05T11:55:29.763067+00:00","updated_at":"2026-07-05T11:55:29.763067+00:00"}