{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZLMQVBRK73BXAUSTYJLM6DORCB","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":"16fb659617ac19695d47fec325a15feee3e4164676c4ef56b054ccb3670241d0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-02T22:28:26Z","title_canon_sha256":"321da576ca3367e304c47f238b742975f92366531ede291ca1b816716a92d61b"},"schema_version":"1.0","source":{"id":"2305.01810","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.01810","created_at":"2026-07-05T06:06:32Z"},{"alias_kind":"arxiv_version","alias_value":"2305.01810v1","created_at":"2026-07-05T06:06:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.01810","created_at":"2026-07-05T06:06:32Z"},{"alias_kind":"pith_short_12","alias_value":"ZLMQVBRK73BX","created_at":"2026-07-05T06:06:32Z"},{"alias_kind":"pith_short_16","alias_value":"ZLMQVBRK73BXAUST","created_at":"2026-07-05T06:06:32Z"},{"alias_kind":"pith_short_8","alias_value":"ZLMQVBRK","created_at":"2026-07-05T06:06:32Z"}],"graph_snapshots":[{"event_id":"sha256:b63470bceeada77af808ff7edd77785890c63b23df41063ce052e48a342477d3","target":"graph","created_at":"2026-07-05T06:06:32Z","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/2305.01810/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, Pre-trained Language Models (PLMs) have shown their superiority by pre-training on unstructured text corpus and then fine-tuning on downstream tasks. On entity-rich textual resources like Wikipedia, Knowledge-Enhanced PLMs (KEPLMs) incorporate the interactions between tokens and mentioned entities in pre-training, and are thus more effective on entity-centric tasks such as entity linking and relation classification. Although exploiting Wikipedia's rich structures to some extent, conventional KEPLMs still neglect a unique layout of the corpus where each Wikipedia page is around","authors_text":"Benjamin Yao, Chengyuan Ma, Derek Liu, Jialong Han, Kyumin Lee, Yichuan Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-02T22:28:26Z","title":"KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.01810","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":"sha256:136eee42c500cce366b93b4b9c22a346576feecc96be13eec87d8cf04200b0b5","target":"record","created_at":"2026-07-05T06:06:32Z","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":"16fb659617ac19695d47fec325a15feee3e4164676c4ef56b054ccb3670241d0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-02T22:28:26Z","title_canon_sha256":"321da576ca3367e304c47f238b742975f92366531ede291ca1b816716a92d61b"},"schema_version":"1.0","source":{"id":"2305.01810","kind":"arxiv","version":1}},"canonical_sha256":"cad90a862afec3705253c256cf0dd1107fec9dd2a71b71c56b22abc34e026e93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cad90a862afec3705253c256cf0dd1107fec9dd2a71b71c56b22abc34e026e93","first_computed_at":"2026-07-05T06:06:32.549614Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:06:32.549614Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ace1zzfBP+Vuq+oYgP7BBjfIIVsD6HGtvkJRuMPOpnPHcPDBZXmBfsmxiLZtMvmDsBjpKN5VpdqqBh852PdoBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:06:32.550037Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.01810","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:136eee42c500cce366b93b4b9c22a346576feecc96be13eec87d8cf04200b0b5","sha256:b63470bceeada77af808ff7edd77785890c63b23df41063ce052e48a342477d3"],"state_sha256":"ba91f4be4c9c4ab03d0eee0087f98d91d0f6c949d4b4e2531a839d9ece64be3d"}