{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:PQFP3HRKBO3FZ4IUU7RBGFASVR","short_pith_number":"pith:PQFP3HRK","canonical_record":{"source":{"id":"1906.01290","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-04T09:15:54Z","cross_cats_sorted":[],"title_canon_sha256":"563e8cc5b7e4cdad5f5550418472f41576fb24583320705ab9b25f3df7bed5e4","abstract_canon_sha256":"33679d06c9226041b9031ed3043f175fc7dd90d5af257a2a1f4aa23c285d259f"},"schema_version":"1.0"},"canonical_sha256":"7c0afd9e2a0bb65cf114a7e2131412ac4e31601fbe14f4baa2ce242fcf6f9de8","source":{"kind":"arxiv","id":"1906.01290","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01290","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01290v1","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01290","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"pith_short_12","alias_value":"PQFP3HRKBO3F","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PQFP3HRKBO3FZ4IU","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PQFP3HRK","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:PQFP3HRKBO3FZ4IUU7RBGFASVR","target":"record","payload":{"canonical_record":{"source":{"id":"1906.01290","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-04T09:15:54Z","cross_cats_sorted":[],"title_canon_sha256":"563e8cc5b7e4cdad5f5550418472f41576fb24583320705ab9b25f3df7bed5e4","abstract_canon_sha256":"33679d06c9226041b9031ed3043f175fc7dd90d5af257a2a1f4aa23c285d259f"},"schema_version":"1.0"},"canonical_sha256":"7c0afd9e2a0bb65cf114a7e2131412ac4e31601fbe14f4baa2ce242fcf6f9de8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:17.130211Z","signature_b64":"tv8cAs+qhvTpcIUPQXY/yGVK3QvsN5wepaVhfPswueOmBtUJk3pTDMsgo4tc/lmXMyc8I/qbx8yKOluVqJDwDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c0afd9e2a0bb65cf114a7e2131412ac4e31601fbe14f4baa2ce242fcf6f9de8","last_reissued_at":"2026-05-17T23:44:17.129572Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:17.129572Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.01290","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R/FGmx97qY1BjuOr35+YsCsKFl49Rb5iowNXh+YM1U9NN2u0hrMiPlDWj2H+Edv4Kf4WjD2aAjXUjO7WTcIQCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:07:47.666985Z"},"content_sha256":"9f6611cfab364b2f7b9e8a2d046ec90f3061dc3ddfd35fa5c675e6f563147a0e","schema_version":"1.0","event_id":"sha256:9f6611cfab364b2f7b9e8a2d046ec90f3061dc3ddfd35fa5c675e6f563147a0e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:PQFP3HRKBO3FZ4IUU7RBGFASVR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Relational Reasoning using Prior Knowledge for Visual Captioning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiebo Luo, Jingyi Hou, Wentian Zhao, Xinxiao Wu, Yayun Qi, Yunde Jia","submitted_at":"2019-06-04T09:15:54Z","abstract_excerpt":"Exploiting relationships among objects has achieved remarkable progress in interpreting images or videos by natural language. Most existing methods resort to first detecting objects and their relationships, and then generating textual descriptions, which heavily depends on pre-trained detectors and leads to performance drop when facing problems of heavy occlusion, tiny-size objects and long-tail in object detection. In addition, the separate procedure of detecting and captioning results in semantic inconsistency between the pre-defined object/relation categories and the target lexical words. W"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01290","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sAxaAKH9L1AyZH1NAAf3BSY5FKN83HYTdPTUUrk4CfO0WF6S1tugsZHXS6Z8ZBfJImRws/2KDSo8TjIDSur5Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:07:47.667330Z"},"content_sha256":"bb6c25d6121dcbbbe3dbb5b82149f1f8f487a77c58d4f53a0d2a715be9fb350b","schema_version":"1.0","event_id":"sha256:bb6c25d6121dcbbbe3dbb5b82149f1f8f487a77c58d4f53a0d2a715be9fb350b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR/bundle.json","state_url":"https://pith.science/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-01T21:07:47Z","links":{"resolver":"https://pith.science/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR","bundle":"https://pith.science/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR/bundle.json","state":"https://pith.science/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PQFP3HRKBO3FZ4IUU7RBGFASVR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PQFP3HRKBO3FZ4IUU7RBGFASVR","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":"33679d06c9226041b9031ed3043f175fc7dd90d5af257a2a1f4aa23c285d259f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-04T09:15:54Z","title_canon_sha256":"563e8cc5b7e4cdad5f5550418472f41576fb24583320705ab9b25f3df7bed5e4"},"schema_version":"1.0","source":{"id":"1906.01290","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01290","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01290v1","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01290","created_at":"2026-05-17T23:44:17Z"},{"alias_kind":"pith_short_12","alias_value":"PQFP3HRKBO3F","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PQFP3HRKBO3FZ4IU","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PQFP3HRK","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:bb6c25d6121dcbbbe3dbb5b82149f1f8f487a77c58d4f53a0d2a715be9fb350b","target":"graph","created_at":"2026-05-17T23:44:17Z","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"},"paper":{"abstract_excerpt":"Exploiting relationships among objects has achieved remarkable progress in interpreting images or videos by natural language. Most existing methods resort to first detecting objects and their relationships, and then generating textual descriptions, which heavily depends on pre-trained detectors and leads to performance drop when facing problems of heavy occlusion, tiny-size objects and long-tail in object detection. In addition, the separate procedure of detecting and captioning results in semantic inconsistency between the pre-defined object/relation categories and the target lexical words. W","authors_text":"Jiebo Luo, Jingyi Hou, Wentian Zhao, Xinxiao Wu, Yayun Qi, Yunde Jia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-04T09:15:54Z","title":"Relational Reasoning using Prior Knowledge for Visual Captioning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01290","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":"sha256:9f6611cfab364b2f7b9e8a2d046ec90f3061dc3ddfd35fa5c675e6f563147a0e","target":"record","created_at":"2026-05-17T23:44:17Z","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":"33679d06c9226041b9031ed3043f175fc7dd90d5af257a2a1f4aa23c285d259f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-04T09:15:54Z","title_canon_sha256":"563e8cc5b7e4cdad5f5550418472f41576fb24583320705ab9b25f3df7bed5e4"},"schema_version":"1.0","source":{"id":"1906.01290","kind":"arxiv","version":1}},"canonical_sha256":"7c0afd9e2a0bb65cf114a7e2131412ac4e31601fbe14f4baa2ce242fcf6f9de8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c0afd9e2a0bb65cf114a7e2131412ac4e31601fbe14f4baa2ce242fcf6f9de8","first_computed_at":"2026-05-17T23:44:17.129572Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:17.129572Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tv8cAs+qhvTpcIUPQXY/yGVK3QvsN5wepaVhfPswueOmBtUJk3pTDMsgo4tc/lmXMyc8I/qbx8yKOluVqJDwDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:17.130211Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.01290","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f6611cfab364b2f7b9e8a2d046ec90f3061dc3ddfd35fa5c675e6f563147a0e","sha256:bb6c25d6121dcbbbe3dbb5b82149f1f8f487a77c58d4f53a0d2a715be9fb350b"],"state_sha256":"5008009dee915e04053c4c1cadf8f861f1ff088ec5c007107edfc4c0a9ad6bb4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EMZYoknpBvL/4xnkom6RjkeaJ0zzbrb45s4JGSyL9RcorFPi0+WROjQ9xCZPOecRNrl1on0Tw2bzthutyuBdDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T21:07:47.669171Z","bundle_sha256":"6bc036b060f6db5588a3886e3c3c56d592030eb07fdaa7b74d3cd66e3d3c3856"}}