{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:5PEJ5ZZXHXBDGEXWSKPDLUMQTG","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":"cc3b9543914da376b6f3082e851e974b1fc8ad4dd70600e5c7c247c521ecb948","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-21T17:05:28Z","title_canon_sha256":"59598e49901d8fa684eeda2da155062b0f9c86824da7e4e853505ca7609d1c89"},"schema_version":"1.0","source":{"id":"1808.07018","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.07018","created_at":"2026-07-05T00:03:54Z"},{"alias_kind":"arxiv_version","alias_value":"1808.07018v5","created_at":"2026-07-05T00:03:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.07018","created_at":"2026-07-05T00:03:54Z"},{"alias_kind":"pith_short_12","alias_value":"5PEJ5ZZXHXBD","created_at":"2026-07-05T00:03:54Z"},{"alias_kind":"pith_short_16","alias_value":"5PEJ5ZZXHXBDGEXW","created_at":"2026-07-05T00:03:54Z"},{"alias_kind":"pith_short_8","alias_value":"5PEJ5ZZX","created_at":"2026-07-05T00:03:54Z"}],"graph_snapshots":[{"event_id":"sha256:24d7915316766065f4f6a501dc284bf57dd5bff5bf48a93bdc703cf8910de2c0","target":"graph","created_at":"2026-07-05T00:03:54Z","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/1808.07018/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge graphs are graphical representations of large databases of facts, which typically suffer from incompleteness. Inferring missing relations (links) between entities (nodes) is the task of link prediction. A recent state-of-the-art approach to link prediction, ConvE, implements a convolutional neural network to extract features from concatenated subject and relation vectors. Whilst results are impressive, the method is unintuitive and poorly understood. We propose a hypernetwork architecture that generates simplified relation-specific convolutional filters that (i) outperforms ConvE and","authors_text":"Carl Allen, Ivana Bala\\v{z}evi\\'c, Timothy M. Hospedales","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-21T17:05:28Z","title":"Hypernetwork Knowledge Graph Embeddings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.07018","kind":"arxiv","version":5},"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":"sha256:3d6ccda77b647159fb8724c03a94326f28f7a4ee49cac3d53525804e1d31b0ca","target":"record","created_at":"2026-07-05T00:03:54Z","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":"cc3b9543914da376b6f3082e851e974b1fc8ad4dd70600e5c7c247c521ecb948","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-21T17:05:28Z","title_canon_sha256":"59598e49901d8fa684eeda2da155062b0f9c86824da7e4e853505ca7609d1c89"},"schema_version":"1.0","source":{"id":"1808.07018","kind":"arxiv","version":5}},"canonical_sha256":"ebc89ee7373dc23312f6929e35d190999f37711ed79008e5c3e8c37fa31f9088","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ebc89ee7373dc23312f6929e35d190999f37711ed79008e5c3e8c37fa31f9088","first_computed_at":"2026-07-05T00:03:54.070849Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:03:54.070849Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8sldH6sJfMlWjiBEwbJz6WnXqDEqoLEe37lUtas2S4vIUU7KeWAYxg0f2E2MeFI7+O4s/9mwu4uVZsKMXCw8AA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:03:54.071391Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.07018","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d6ccda77b647159fb8724c03a94326f28f7a4ee49cac3d53525804e1d31b0ca","sha256:24d7915316766065f4f6a501dc284bf57dd5bff5bf48a93bdc703cf8910de2c0"],"state_sha256":"da057740081347e3349f6d5416bfd6229ffa634e15f0fe5a2e82d95e59322167"}