{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:XS2Y6PRRLAW35W5GVOZ3GUWPSF","short_pith_number":"pith:XS2Y6PRR","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"},"canonical_sha256":"bcb58f3e31582dbedba6abb3b352cf9156437e488a3ea1e07b31152d4ec6ea7c","source":{"kind":"arxiv","id":"2607.10197","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.10197","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"arxiv_version","alias_value":"2607.10197v1","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.10197","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"pith_short_12","alias_value":"XS2Y6PRRLAW3","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"pith_short_16","alias_value":"XS2Y6PRRLAW35W5G","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"pith_short_8","alias_value":"XS2Y6PRR","created_at":"2026-07-14T01:20:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:XS2Y6PRRLAW35W5GVOZ3GUWPSF","target":"record","payload":{"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"},"canonical_sha256":"bcb58f3e31582dbedba6abb3b352cf9156437e488a3ea1e07b31152d4ec6ea7c","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"},"source_kind":"arxiv","source_id":"2607.10197","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":"2026-07-14T01:20:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hlYid+y0bAycyNVYKYxwijP2SUYPO/ik1gCin76H9OHj0v+yw6yXRX55iYmGe4gWUau7MNOLzwRiaRVYdeXVAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:09:30.933631Z"},"content_sha256":"0ff40679c93e70694d95ce29d7ff8a7a9236f1912a188fefaaf6adc852c9cf54","schema_version":"1.0","event_id":"sha256:0ff40679c93e70694d95ce29d7ff8a7a9236f1912a188fefaaf6adc852c9cf54"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:XS2Y6PRRLAW35W5GVOZ3GUWPSF","target":"graph","payload":{"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-14T01:20:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VauUAa4qyg2Rac824RWq1p/UBmu/g4pla4cT0YIpJsvShHpmUUJ+wyPEkXk2VI7cK6l6UeLEMlTVATQtN1YwBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:09:30.934219Z"},"content_sha256":"510dfcfc767e3ec9ea0d903ec4a48945437f859a2557602fd5790125fe67b358","schema_version":"1.0","event_id":"sha256:510dfcfc767e3ec9ea0d903ec4a48945437f859a2557602fd5790125fe67b358"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/bundle.json","state_url":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/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":"2026-08-08T20:09:30Z","links":{"resolver":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF","bundle":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/bundle.json","state":"https://pith.science/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XS2Y6PRRLAW35W5GVOZ3GUWPSF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XS2Y6PRRLAW35W5GVOZ3GUWPSF","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":"d450521023b9c67084cc10335de0f8f49052dc63d7038741a6baac3804f0bae9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-11T08:22:17Z","title_canon_sha256":"7d304874b3faf08ccab6abdf26a441f04960554ce4327ad934f5d674ec656827"},"schema_version":"1.0","source":{"id":"2607.10197","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.10197","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"arxiv_version","alias_value":"2607.10197v1","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.10197","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"pith_short_12","alias_value":"XS2Y6PRRLAW3","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"pith_short_16","alias_value":"XS2Y6PRRLAW35W5G","created_at":"2026-07-14T01:20:30Z"},{"alias_kind":"pith_short_8","alias_value":"XS2Y6PRR","created_at":"2026-07-14T01:20:30Z"}],"graph_snapshots":[{"event_id":"sha256:510dfcfc767e3ec9ea0d903ec4a48945437f859a2557602fd5790125fe67b358","target":"graph","created_at":"2026-07-14T01:20:30Z","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/2607.10197/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"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","authors_text":"Daniel Hern\\'andez, Jiaxin Pan, Osama Mohammed, Steffen Staab","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-11T08:22:17Z","title":"GRATE: Temporal Extensions for Inductive KG Foundation Models via Gated Rotary Attention"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.10197","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":"sha256:0ff40679c93e70694d95ce29d7ff8a7a9236f1912a188fefaaf6adc852c9cf54","target":"record","created_at":"2026-07-14T01:20:30Z","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":"d450521023b9c67084cc10335de0f8f49052dc63d7038741a6baac3804f0bae9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-11T08:22:17Z","title_canon_sha256":"7d304874b3faf08ccab6abdf26a441f04960554ce4327ad934f5d674ec656827"},"schema_version":"1.0","source":{"id":"2607.10197","kind":"arxiv","version":1}},"canonical_sha256":"bcb58f3e31582dbedba6abb3b352cf9156437e488a3ea1e07b31152d4ec6ea7c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bcb58f3e31582dbedba6abb3b352cf9156437e488a3ea1e07b31152d4ec6ea7c","first_computed_at":"2026-07-14T01:20:30.251295Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T01:20:30.251295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"z3A4hl7HmrTEgC4zxxHqzR53R1bCF6krDoOHw5G2Rnf4GIfBn9SE2yfcK93fSUZPPQC6LqegUh/8FwharVN/BA==","signature_status":"signed_v1","signed_at":"2026-07-14T01:20:30.252333Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.10197","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ff40679c93e70694d95ce29d7ff8a7a9236f1912a188fefaaf6adc852c9cf54","sha256:510dfcfc767e3ec9ea0d903ec4a48945437f859a2557602fd5790125fe67b358"],"state_sha256":"90d396899aba9253cc93f7a81e3f2dc236be83f896b2612c0a553219598a70f0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6zHj0zUn1GXyfnUOqHvKKuVUXR5HA4eS9VHUWA8nV74EWMnTmOatkMM+BrRL5u6ynfuiWbMpdPKuPkLe0yp1DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:09:30.938799Z","bundle_sha256":"12e341c9386c64fee7b9b69082169f03eb1b21b9707dec6aab0a8b477133d788"}}