{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XS2Y6PRRLAW35W5GVOZ3GUWPSF","short_pith_number":"pith:XS2Y6PRR","schema_version":"1.0","canonical_sha256":"bcb58f3e31582dbedba6abb3b352cf9156437e488a3ea1e07b31152d4ec6ea7c","source":{"kind":"arxiv","id":"2607.10197","version":1},"attestation_state":"computed","paper":{"title":"GRATE: Temporal Extensions for Inductive KG Foundation Models via Gated Rotary Attention","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Daniel Hern\\'andez, Jiaxin Pan, Osama Mohammed, Steffen Staab","submitted_at":"2026-07-11T08:22:17Z","abstract_excerpt":"Knowledge graph foundation models such as Ultra and Trix achieve strong inductive transfer by learning relation-graph representations that generalise to unseen entities and relations. Extending this transferability to temporal knowledge graphs (TKGs) remains challenging: existing temporal models tie their parameters to dataset-specific entities, relations, or timestamps and are not designed to transfer to TKGs with disjoint vocabularies. We propose GRATE (Gated Rotary Attention for Temporal Encoding), an entity-side message function that adds no learnable parameters and encodes time through re"},"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":"2607.10197","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-11T08:22:17Z","cross_cats_sorted":[],"title_canon_sha256":"7d304874b3faf08ccab6abdf26a441f04960554ce4327ad934f5d674ec656827","abstract_canon_sha256":"d450521023b9c67084cc10335de0f8f49052dc63d7038741a6baac3804f0bae9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-14T01:20:30.252333Z","signature_b64":"z3A4hl7HmrTEgC4zxxHqzR53R1bCF6krDoOHw5G2Rnf4GIfBn9SE2yfcK93fSUZPPQC6LqegUh/8FwharVN/BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bcb58f3e31582dbedba6abb3b352cf9156437e488a3ea1e07b31152d4ec6ea7c","last_reissued_at":"2026-07-14T01:20:30.251295Z","signature_status":"signed_v1","first_computed_at":"2026-07-14T01:20:30.251295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GRATE: Temporal Extensions for Inductive KG Foundation Models via Gated Rotary Attention","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Daniel Hern\\'andez, Jiaxin Pan, Osama Mohammed, Steffen Staab","submitted_at":"2026-07-11T08:22:17Z","abstract_excerpt":"Knowledge graph foundation models such as Ultra and Trix achieve strong inductive transfer by learning relation-graph representations that generalise to unseen entities and relations. Extending this transferability to temporal knowledge graphs (TKGs) remains challenging: existing temporal models tie their parameters to dataset-specific entities, relations, or timestamps and are not designed to transfer to TKGs with disjoint vocabularies. We propose GRATE (Gated Rotary Attention for Temporal Encoding), an entity-side message function that adds no learnable parameters and encodes time through re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.10197","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.10197/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.10197","created_at":"2026-07-14T01:20:30.251772+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.10197v1","created_at":"2026-07-14T01:20:30.251772+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.10197","created_at":"2026-07-14T01:20:30.251772+00:00"},{"alias_kind":"pith_short_12","alias_value":"XS2Y6PRRLAW3","created_at":"2026-07-14T01:20:30.251772+00:00"},{"alias_kind":"pith_short_16","alias_value":"XS2Y6PRRLAW35W5G","created_at":"2026-07-14T01:20:30.251772+00:00"},{"alias_kind":"pith_short_8","alias_value":"XS2Y6PRR","created_at":"2026-07-14T01:20:30.251772+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/XS2Y6PRRLAW35W5GVOZ3GUWPSF","json":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF.json","graph_json":"https://pith.science/api/pith-number/XS2Y6PRRLAW35W5GVOZ3GUWPSF/graph.json","events_json":"https://pith.science/api/pith-number/XS2Y6PRRLAW35W5GVOZ3GUWPSF/events.json","paper":"https://pith.science/paper/XS2Y6PRR"},"agent_actions":{"view_html":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF","download_json":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF.json","view_paper":"https://pith.science/paper/XS2Y6PRR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.10197&json=true","fetch_graph":"https://pith.science/api/pith-number/XS2Y6PRRLAW35W5GVOZ3GUWPSF/graph.json","fetch_events":"https://pith.science/api/pith-number/XS2Y6PRRLAW35W5GVOZ3GUWPSF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/action/storage_attestation","attest_author":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/action/author_attestation","sign_citation":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/action/citation_signature","submit_replication":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/action/replication_record"}},"created_at":"2026-07-14T01:20:30.251772+00:00","updated_at":"2026-07-14T01:20:30.251772+00:00"}