{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:APDZSATVQ36NFNNLEWUULSQV3J","short_pith_number":"pith:APDZSATV","schema_version":"1.0","canonical_sha256":"03c799027586fcd2b5ab25a945ca15da5d7cd017d05c17007ec580d7c124ac44","source":{"kind":"arxiv","id":"2301.00436","version":3},"attestation_state":"computed","paper":{"title":"Hierarchical Explanations for Video Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Nanne van Noord, Sadaf Gulshad, Teng Long","submitted_at":"2023-01-01T16:24:12Z","abstract_excerpt":"To interpret deep neural networks, one main approach is to dissect the visual input and find the prototypical parts responsible for the classification. However, existing methods often ignore the hierarchical relationship between these prototypes, and thus can not explain semantic concepts at both higher level (e.g., water sports) and lower level (e.g., swimming). In this paper inspired by human cognition system, we leverage hierarchal information to deal with uncertainty: When we observe water and human activity, but no definitive action it can be recognized as the water sports parent class. O"},"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":"2301.00436","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-01T16:24:12Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"5f5740b78a8ab528788c0cb464603778a947dfe8cdec67e00c4e690f57ef6681","abstract_canon_sha256":"3c5c8bf0af297402053da49c6e4e67f869c1d422f5e4817bdb085173bbe97255"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:57:35.337005Z","signature_b64":"y+MNreURyaCZHTVkXD9a5oulFsbnsIMcldck8ussjIk68dFZK/J0IH3/5TCoBdErFTFUW8m6YRs0MXnxTSHiDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"03c799027586fcd2b5ab25a945ca15da5d7cd017d05c17007ec580d7c124ac44","last_reissued_at":"2026-07-05T05:57:35.336476Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:57:35.336476Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hierarchical Explanations for Video Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Nanne van Noord, Sadaf Gulshad, Teng Long","submitted_at":"2023-01-01T16:24:12Z","abstract_excerpt":"To interpret deep neural networks, one main approach is to dissect the visual input and find the prototypical parts responsible for the classification. However, existing methods often ignore the hierarchical relationship between these prototypes, and thus can not explain semantic concepts at both higher level (e.g., water sports) and lower level (e.g., swimming). In this paper inspired by human cognition system, we leverage hierarchal information to deal with uncertainty: When we observe water and human activity, but no definitive action it can be recognized as the water sports parent class. O"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.00436","kind":"arxiv","version":3},"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/2301.00436/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":"2301.00436","created_at":"2026-07-05T05:57:35.336539+00:00"},{"alias_kind":"arxiv_version","alias_value":"2301.00436v3","created_at":"2026-07-05T05:57:35.336539+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.00436","created_at":"2026-07-05T05:57:35.336539+00:00"},{"alias_kind":"pith_short_12","alias_value":"APDZSATVQ36N","created_at":"2026-07-05T05:57:35.336539+00:00"},{"alias_kind":"pith_short_16","alias_value":"APDZSATVQ36NFNNL","created_at":"2026-07-05T05:57:35.336539+00:00"},{"alias_kind":"pith_short_8","alias_value":"APDZSATV","created_at":"2026-07-05T05:57:35.336539+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/APDZSATVQ36NFNNLEWUULSQV3J","json":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J.json","graph_json":"https://pith.science/api/pith-number/APDZSATVQ36NFNNLEWUULSQV3J/graph.json","events_json":"https://pith.science/api/pith-number/APDZSATVQ36NFNNLEWUULSQV3J/events.json","paper":"https://pith.science/paper/APDZSATV"},"agent_actions":{"view_html":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J","download_json":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J.json","view_paper":"https://pith.science/paper/APDZSATV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2301.00436&json=true","fetch_graph":"https://pith.science/api/pith-number/APDZSATVQ36NFNNLEWUULSQV3J/graph.json","fetch_events":"https://pith.science/api/pith-number/APDZSATVQ36NFNNLEWUULSQV3J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J/action/storage_attestation","attest_author":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J/action/author_attestation","sign_citation":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J/action/citation_signature","submit_replication":"https://pith.science/pith/APDZSATVQ36NFNNLEWUULSQV3J/action/replication_record"}},"created_at":"2026-07-05T05:57:35.336539+00:00","updated_at":"2026-07-05T05:57:35.336539+00:00"}