{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:I24VOCXRYZWAJVDP5X5JKE3YQQ","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":"463a020423023df60aadc49134a7a56159e61c5043d0f7abd625f43933b44723","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T15:09:32Z","title_canon_sha256":"8aa0bb8e8c84fc157ee93386d676cba1833d66d48c063f70da9456331353a641"},"schema_version":"1.0","source":{"id":"2110.02834","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02834","created_at":"2026-07-05T03:20:30Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02834v1","created_at":"2026-07-05T03:20:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02834","created_at":"2026-07-05T03:20:30Z"},{"alias_kind":"pith_short_12","alias_value":"I24VOCXRYZWA","created_at":"2026-07-05T03:20:30Z"},{"alias_kind":"pith_short_16","alias_value":"I24VOCXRYZWAJVDP","created_at":"2026-07-05T03:20:30Z"},{"alias_kind":"pith_short_8","alias_value":"I24VOCXR","created_at":"2026-07-05T03:20:30Z"}],"graph_snapshots":[{"event_id":"sha256:d8b1e1f222f48419e4d9bc4abe9aa6515c28280aeb6649761f4b64e25c1a411a","target":"graph","created_at":"2026-07-05T03:20:30Z","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/2110.02834/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning good representations on multi-relational graphs is essential to knowledge base completion (KBC). In this paper, we propose a new self-supervised training objective for multi-relational graph representation learning, via simply incorporating relation prediction into the commonly used 1vsAll objective. The new training objective contains not only terms for predicting the subject and object of a given triple, but also a term for predicting the relation type. We analyse how this new objective impacts multi-relational learning in KBC: experiments on a variety of datasets and models show th","authors_text":"Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Yihong Chen","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T15:09:32Z","title":"Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02834","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":"sha256:06a5d4901d81f84adf9c41a8c84bc9362abcb1da515b4832c71438f1d0827531","target":"record","created_at":"2026-07-05T03:20:30Z","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":"463a020423023df60aadc49134a7a56159e61c5043d0f7abd625f43933b44723","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T15:09:32Z","title_canon_sha256":"8aa0bb8e8c84fc157ee93386d676cba1833d66d48c063f70da9456331353a641"},"schema_version":"1.0","source":{"id":"2110.02834","kind":"arxiv","version":1}},"canonical_sha256":"46b9570af1c66c04d46fedfa9513788406b82ceb597497512c2308449e901803","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46b9570af1c66c04d46fedfa9513788406b82ceb597497512c2308449e901803","first_computed_at":"2026-07-05T03:20:30.381030Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:20:30.381030Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yvC8SF5j2eNVO9h8GT4qZN7DS9BPvIF9OHONKcH1MWfvZUjPgb9ejUsudY2zaYxoVnNTSyLWiqkS6O4VGP3eCA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:20:30.381478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.02834","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:06a5d4901d81f84adf9c41a8c84bc9362abcb1da515b4832c71438f1d0827531","sha256:d8b1e1f222f48419e4d9bc4abe9aa6515c28280aeb6649761f4b64e25c1a411a"],"state_sha256":"2ebbf5af45a0d7d3765c01ad70adcf535719a52b36280d917bf14268a70236f6"}