{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:GVDYD5V5RJXKWF52U524UU25LQ","short_pith_number":"pith:GVDYD5V5","canonical_record":{"source":{"id":"2302.06057","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T02:29:11Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"98de60a2e481c88fd03f45b0c81537cf894efc211adb585fda71221e0bdd01c6","abstract_canon_sha256":"2c27ddfa9c0d1b7b44eabd5d109ee8c69d143f4b36bd6b181e7c81bbf467e500"},"schema_version":"1.0"},"canonical_sha256":"354781f6bd8a6eab17baa775ca535d5c228b7275e5a5b1f18c437dd5ec7ff019","source":{"kind":"arxiv","id":"2302.06057","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.06057","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"arxiv_version","alias_value":"2302.06057v2","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.06057","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"pith_short_12","alias_value":"GVDYD5V5RJXK","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"pith_short_16","alias_value":"GVDYD5V5RJXKWF52","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"pith_short_8","alias_value":"GVDYD5V5","created_at":"2026-07-05T05:42:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:GVDYD5V5RJXKWF52U524UU25LQ","target":"record","payload":{"canonical_record":{"source":{"id":"2302.06057","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T02:29:11Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"98de60a2e481c88fd03f45b0c81537cf894efc211adb585fda71221e0bdd01c6","abstract_canon_sha256":"2c27ddfa9c0d1b7b44eabd5d109ee8c69d143f4b36bd6b181e7c81bbf467e500"},"schema_version":"1.0"},"canonical_sha256":"354781f6bd8a6eab17baa775ca535d5c228b7275e5a5b1f18c437dd5ec7ff019","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:42:30.945822Z","signature_b64":"GHw9FdHJczv4akgDHXr5j5DWkq/RK5VyfoubKbUzyZhCSfuQt8UZlQS/6CPAAHamsvX9vhXETXzxhY5dNwWtBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"354781f6bd8a6eab17baa775ca535d5c228b7275e5a5b1f18c437dd5ec7ff019","last_reissued_at":"2026-07-05T05:42:30.945382Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:42:30.945382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.06057","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:42:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gQG0cfqXm13xiEG/Y1iZ5Luk85A1sxWgzXHeHJw8t4OrjpoJhMVU/Xiim2zUy+4SvUocdpEXb9BVXFL2kvlwBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T16:02:37.157646Z"},"content_sha256":"06e12a1fc36c0f2c458a140dc279ded935a668496160374d00d9acbae0fdc591","schema_version":"1.0","event_id":"sha256:06e12a1fc36c0f2c458a140dc279ded935a668496160374d00d9acbae0fdc591"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:GVDYD5V5RJXKWF52U524UU25LQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TIGER: Temporal Interaction Graph Embedding with Restarts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.LG","authors_text":"Xuehao Zheng, Yangyong Zhu, Yao Zhang, Yiheng Sun, Yongxiang Liao, Yucheng Jin, Yun Xiong","submitted_at":"2023-02-13T02:29:11Z","abstract_excerpt":"Temporal interaction graphs (TIGs), consisting of sequences of timestamped interaction events, are prevalent in fields like e-commerce and social networks. To better learn dynamic node embeddings that vary over time, researchers have proposed a series of temporal graph neural networks for TIGs. However, due to the entangled temporal and structural dependencies, existing methods have to process the sequence of events chronologically and consecutively to ensure node representations are up-to-date. This prevents existing models from parallelization and reduces their flexibility in industrial appl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.06057","kind":"arxiv","version":2},"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/2302.06057/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:42:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ssdEBQdjTH4jaC0Z9tVAA28jYv4jREM3BaltichS06YfHpQyIn90f2amJraPcmuUhD1YR12P5crglICFq0FRCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T16:02:37.158157Z"},"content_sha256":"468313269f5b4943e0a1331aff7268818819da4c1ec7d913cc29b499823fce55","schema_version":"1.0","event_id":"sha256:468313269f5b4943e0a1331aff7268818819da4c1ec7d913cc29b499823fce55"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GVDYD5V5RJXKWF52U524UU25LQ/bundle.json","state_url":"https://pith.science/pith/GVDYD5V5RJXKWF52U524UU25LQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GVDYD5V5RJXKWF52U524UU25LQ/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":"2026-08-14T16:02:37Z","links":{"resolver":"https://pith.science/pith/GVDYD5V5RJXKWF52U524UU25LQ","bundle":"https://pith.science/pith/GVDYD5V5RJXKWF52U524UU25LQ/bundle.json","state":"https://pith.science/pith/GVDYD5V5RJXKWF52U524UU25LQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GVDYD5V5RJXKWF52U524UU25LQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GVDYD5V5RJXKWF52U524UU25LQ","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":"2c27ddfa9c0d1b7b44eabd5d109ee8c69d143f4b36bd6b181e7c81bbf467e500","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T02:29:11Z","title_canon_sha256":"98de60a2e481c88fd03f45b0c81537cf894efc211adb585fda71221e0bdd01c6"},"schema_version":"1.0","source":{"id":"2302.06057","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.06057","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"arxiv_version","alias_value":"2302.06057v2","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.06057","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"pith_short_12","alias_value":"GVDYD5V5RJXK","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"pith_short_16","alias_value":"GVDYD5V5RJXKWF52","created_at":"2026-07-05T05:42:30Z"},{"alias_kind":"pith_short_8","alias_value":"GVDYD5V5","created_at":"2026-07-05T05:42:30Z"}],"graph_snapshots":[{"event_id":"sha256:468313269f5b4943e0a1331aff7268818819da4c1ec7d913cc29b499823fce55","target":"graph","created_at":"2026-07-05T05:42:30Z","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/2302.06057/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Temporal interaction graphs (TIGs), consisting of sequences of timestamped interaction events, are prevalent in fields like e-commerce and social networks. To better learn dynamic node embeddings that vary over time, researchers have proposed a series of temporal graph neural networks for TIGs. However, due to the entangled temporal and structural dependencies, existing methods have to process the sequence of events chronologically and consecutively to ensure node representations are up-to-date. This prevents existing models from parallelization and reduces their flexibility in industrial appl","authors_text":"Xuehao Zheng, Yangyong Zhu, Yao Zhang, Yiheng Sun, Yongxiang Liao, Yucheng Jin, Yun Xiong","cross_cats":["cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T02:29:11Z","title":"TIGER: Temporal Interaction Graph Embedding with Restarts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.06057","kind":"arxiv","version":2},"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":"sha256:06e12a1fc36c0f2c458a140dc279ded935a668496160374d00d9acbae0fdc591","target":"record","created_at":"2026-07-05T05:42:30Z","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":"2c27ddfa9c0d1b7b44eabd5d109ee8c69d143f4b36bd6b181e7c81bbf467e500","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T02:29:11Z","title_canon_sha256":"98de60a2e481c88fd03f45b0c81537cf894efc211adb585fda71221e0bdd01c6"},"schema_version":"1.0","source":{"id":"2302.06057","kind":"arxiv","version":2}},"canonical_sha256":"354781f6bd8a6eab17baa775ca535d5c228b7275e5a5b1f18c437dd5ec7ff019","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"354781f6bd8a6eab17baa775ca535d5c228b7275e5a5b1f18c437dd5ec7ff019","first_computed_at":"2026-07-05T05:42:30.945382Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:42:30.945382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GHw9FdHJczv4akgDHXr5j5DWkq/RK5VyfoubKbUzyZhCSfuQt8UZlQS/6CPAAHamsvX9vhXETXzxhY5dNwWtBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:42:30.945822Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.06057","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:06e12a1fc36c0f2c458a140dc279ded935a668496160374d00d9acbae0fdc591","sha256:468313269f5b4943e0a1331aff7268818819da4c1ec7d913cc29b499823fce55"],"state_sha256":"3390ac2dbd4ddd53edbab8953a3b019351a1399f122c950d23c3ce57cdde6207"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jU/YaWIDT2lFq0NGMcbH3tUG5hu95klCnLzj7liU/bkOLHxLqlPSQJytya5UnZ6/2tGQvVmxmSgLU/X4NbdKAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T16:02:37.195879Z","bundle_sha256":"a0e5cfe90336347b88e2fc323c484cd601e5321dd6399e7ce1c7fc45714adc37"}}