{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:4FDSABKYFBX3YNY5QGZAQHDFXV","short_pith_number":"pith:4FDSABKY","schema_version":"1.0","canonical_sha256":"e147200558286fbc371d81b2081c65bd4a1764fc582ec33ce63b46654096fb3e","source":{"kind":"arxiv","id":"1608.00187","version":1},"attestation_state":"computed","paper":{"title":"Visual Relationship Detection with Language Priors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cewu Lu, Li Fei-Fei, Michael Bernstein, Ranjay Krishna","submitted_at":"2016-07-31T05:54:13Z","abstract_excerpt":"Visual relationships capture a wide variety of interactions between pairs of objects in images (e.g. \"man riding bicycle\" and \"man pushing bicycle\"). Consequently, the set of possible relationships is extremely large and it is difficult to obtain sufficient training examples for all possible relationships. Because of this limitation, previous work on visual relationship detection has concentrated on predicting only a handful of relationships. Though most relationships are infrequent, their objects (e.g. \"man\" and \"bicycle\") and predicates (e.g. \"riding\" and \"pushing\") independently occur more "},"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":"1608.00187","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-07-31T05:54:13Z","cross_cats_sorted":[],"title_canon_sha256":"57721208883ca26717c73c06632f38ead02a2e0d8891d6d1c90070b38d4dd0bc","abstract_canon_sha256":"3ba6e3c3deb80557a8a1f01334f52ce7642951bf831e01964c49220c36b0d1f3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:10:12.301453Z","signature_b64":"gb3YOhLL2CIsatMBS0LKhxM1NxZID72uHp/CTB+RkLLg1Im+rTX8YN3tDhBND1QDkXfLdYtPxbak5vJBhtNLCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e147200558286fbc371d81b2081c65bd4a1764fc582ec33ce63b46654096fb3e","last_reissued_at":"2026-05-18T01:10:12.300807Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:10:12.300807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Visual Relationship Detection with Language Priors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cewu Lu, Li Fei-Fei, Michael Bernstein, Ranjay Krishna","submitted_at":"2016-07-31T05:54:13Z","abstract_excerpt":"Visual relationships capture a wide variety of interactions between pairs of objects in images (e.g. \"man riding bicycle\" and \"man pushing bicycle\"). Consequently, the set of possible relationships is extremely large and it is difficult to obtain sufficient training examples for all possible relationships. Because of this limitation, previous work on visual relationship detection has concentrated on predicting only a handful of relationships. Though most relationships are infrequent, their objects (e.g. \"man\" and \"bicycle\") and predicates (e.g. \"riding\" and \"pushing\") independently occur more "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.00187","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":""},"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":"1608.00187","created_at":"2026-05-18T01:10:12.300916+00:00"},{"alias_kind":"arxiv_version","alias_value":"1608.00187v1","created_at":"2026-05-18T01:10:12.300916+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.00187","created_at":"2026-05-18T01:10:12.300916+00:00"},{"alias_kind":"pith_short_12","alias_value":"4FDSABKYFBX3","created_at":"2026-05-18T12:29:58.707656+00:00"},{"alias_kind":"pith_short_16","alias_value":"4FDSABKYFBX3YNY5","created_at":"2026-05-18T12:29:58.707656+00:00"},{"alias_kind":"pith_short_8","alias_value":"4FDSABKY","created_at":"2026-05-18T12:29:58.707656+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/4FDSABKYFBX3YNY5QGZAQHDFXV","json":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV.json","graph_json":"https://pith.science/api/pith-number/4FDSABKYFBX3YNY5QGZAQHDFXV/graph.json","events_json":"https://pith.science/api/pith-number/4FDSABKYFBX3YNY5QGZAQHDFXV/events.json","paper":"https://pith.science/paper/4FDSABKY"},"agent_actions":{"view_html":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV","download_json":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV.json","view_paper":"https://pith.science/paper/4FDSABKY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1608.00187&json=true","fetch_graph":"https://pith.science/api/pith-number/4FDSABKYFBX3YNY5QGZAQHDFXV/graph.json","fetch_events":"https://pith.science/api/pith-number/4FDSABKYFBX3YNY5QGZAQHDFXV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV/action/storage_attestation","attest_author":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV/action/author_attestation","sign_citation":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV/action/citation_signature","submit_replication":"https://pith.science/pith/4FDSABKYFBX3YNY5QGZAQHDFXV/action/replication_record"}},"created_at":"2026-05-18T01:10:12.300916+00:00","updated_at":"2026-05-18T01:10:12.300916+00:00"}