{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KS7FBBDZXGE6A3GXS62DGHA5EJ","short_pith_number":"pith:KS7FBBDZ","canonical_record":{"source":{"id":"2212.05767","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-12-12T08:40:04Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"c680342e6f14797199cab1c987f9f2be9d7fd22d8f79467b2d558469712fd787","abstract_canon_sha256":"337a00de8b9320fb5224f23974ea8b953fbf9c938f5a00f70413cca6f401529d"},"schema_version":"1.0"},"canonical_sha256":"54be508479b989e06cd797b4331c1d2246f1b0228a7afcd14f42a4c916291029","source":{"kind":"arxiv","id":"2212.05767","version":7},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.05767","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"arxiv_version","alias_value":"2212.05767v7","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.05767","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"pith_short_12","alias_value":"KS7FBBDZXGE6","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"pith_short_16","alias_value":"KS7FBBDZXGE6A3GX","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"pith_short_8","alias_value":"KS7FBBDZ","created_at":"2026-07-05T09:26:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KS7FBBDZXGE6A3GXS62DGHA5EJ","target":"record","payload":{"canonical_record":{"source":{"id":"2212.05767","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-12-12T08:40:04Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"c680342e6f14797199cab1c987f9f2be9d7fd22d8f79467b2d558469712fd787","abstract_canon_sha256":"337a00de8b9320fb5224f23974ea8b953fbf9c938f5a00f70413cca6f401529d"},"schema_version":"1.0"},"canonical_sha256":"54be508479b989e06cd797b4331c1d2246f1b0228a7afcd14f42a4c916291029","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:26:18.892497Z","signature_b64":"tyRPNLuLHTTJ4yfkW0etOUEw3v/5Iu/UKZWRamnusKVCmm8stl8P3IaD8zF0kn1ZwhWNEBBErgM3VSojl2xJDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"54be508479b989e06cd797b4331c1d2246f1b0228a7afcd14f42a4c916291029","last_reissued_at":"2026-07-05T09:26:18.892020Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:26:18.892020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.05767","source_version":7,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:26:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ROTXfrzLhVerHMw4VzU4AzNKQDOfpHFxKfg7AheAjLLWXK1CxW9L55qkU6jIZXG85kQNowLW4WeKXfvN2fbtBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:32:06.290649Z"},"content_sha256":"43a846c32e06206740d46576c9f503562ece4a6c56370b9e6d9d1774cd73c454","schema_version":"1.0","event_id":"sha256:43a846c32e06206740d46576c9f503562ece4a6c56370b9e6d9d1774cd73c454"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KS7FBBDZXGE6A3GXS62DGHA5EJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.IR"],"primary_cat":"cs.AI","authors_text":"Fuchun Sun, Ke Liang, Lingyuan Meng, Meng Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Xinwang Liu, Yue Liu","submitted_at":"2022-12-12T08:40:04Z","abstract_excerpt":"Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research direction. It has been proven to significantly benefit the usage of KGs in many AI applications, such as question answering, recommendation systems, and etc. According to the graph types, existing KGR models can be roughly divided into three categories, i.e., static models, temporal models, and multi-modal models. Early works in this domain mainly focus on static KGR, and recent works try to leverage the temporal and mu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.05767","kind":"arxiv","version":7},"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/2212.05767/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":"2026-07-05T09:26:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6muXX3Z9Qks0P7KMFQYQhw1WnjTMWimfTw7YcjapzWBPOWs0QYUKkOjTvxbKXufeN8HyWCL6B99AnNZVIInSAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:32:06.291179Z"},"content_sha256":"bb49d474db0816c5ee1f66151d6615096297d81a1c990eea88a1a3e126029149","schema_version":"1.0","event_id":"sha256:bb49d474db0816c5ee1f66151d6615096297d81a1c990eea88a1a3e126029149"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ/bundle.json","state_url":"https://pith.science/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ/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":"2026-08-09T07:32:06Z","links":{"resolver":"https://pith.science/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ","bundle":"https://pith.science/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ/bundle.json","state":"https://pith.science/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KS7FBBDZXGE6A3GXS62DGHA5EJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KS7FBBDZXGE6A3GXS62DGHA5EJ","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":"337a00de8b9320fb5224f23974ea8b953fbf9c938f5a00f70413cca6f401529d","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-12-12T08:40:04Z","title_canon_sha256":"c680342e6f14797199cab1c987f9f2be9d7fd22d8f79467b2d558469712fd787"},"schema_version":"1.0","source":{"id":"2212.05767","kind":"arxiv","version":7}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.05767","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"arxiv_version","alias_value":"2212.05767v7","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.05767","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"pith_short_12","alias_value":"KS7FBBDZXGE6","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"pith_short_16","alias_value":"KS7FBBDZXGE6A3GX","created_at":"2026-07-05T09:26:18Z"},{"alias_kind":"pith_short_8","alias_value":"KS7FBBDZ","created_at":"2026-07-05T09:26:18Z"}],"graph_snapshots":[{"event_id":"sha256:bb49d474db0816c5ee1f66151d6615096297d81a1c990eea88a1a3e126029149","target":"graph","created_at":"2026-07-05T09:26:18Z","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/2212.05767/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research direction. It has been proven to significantly benefit the usage of KGs in many AI applications, such as question answering, recommendation systems, and etc. According to the graph types, existing KGR models can be roughly divided into three categories, i.e., static models, temporal models, and multi-modal models. Early works in this domain mainly focus on static KGR, and recent works try to leverage the temporal and mu","authors_text":"Fuchun Sun, Ke Liang, Lingyuan Meng, Meng Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Xinwang Liu, Yue Liu","cross_cats":["cs.CL","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-12-12T08:40:04Z","title":"A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodal"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.05767","kind":"arxiv","version":7},"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":"sha256:43a846c32e06206740d46576c9f503562ece4a6c56370b9e6d9d1774cd73c454","target":"record","created_at":"2026-07-05T09:26:18Z","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":"337a00de8b9320fb5224f23974ea8b953fbf9c938f5a00f70413cca6f401529d","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-12-12T08:40:04Z","title_canon_sha256":"c680342e6f14797199cab1c987f9f2be9d7fd22d8f79467b2d558469712fd787"},"schema_version":"1.0","source":{"id":"2212.05767","kind":"arxiv","version":7}},"canonical_sha256":"54be508479b989e06cd797b4331c1d2246f1b0228a7afcd14f42a4c916291029","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"54be508479b989e06cd797b4331c1d2246f1b0228a7afcd14f42a4c916291029","first_computed_at":"2026-07-05T09:26:18.892020Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:18.892020Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tyRPNLuLHTTJ4yfkW0etOUEw3v/5Iu/UKZWRamnusKVCmm8stl8P3IaD8zF0kn1ZwhWNEBBErgM3VSojl2xJDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:18.892497Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.05767","source_kind":"arxiv","source_version":7}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:43a846c32e06206740d46576c9f503562ece4a6c56370b9e6d9d1774cd73c454","sha256:bb49d474db0816c5ee1f66151d6615096297d81a1c990eea88a1a3e126029149"],"state_sha256":"f0865fc7ef80f939b032e1a705e4c9e9a23570ed35bf1a787dc4e6bef5b453f1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6q+rwC9bD/FA8zpTREErYpLE//TBZar0EjeTOvfs2Z5uXqRjHlMNeL33RHQQgCQY4xgfpeDK+uopqLZlzyJaDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T07:32:06.297410Z","bundle_sha256":"3866a09e3d1eeb7062c3a842927ee201190c9ed0fe372d701d4b671e6c2aa290"}}