{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IU65IOKQDM6KVSKDRI4YUSTOAF","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":"58800a61ba6e090238fb8fdf988d706206a6bc78b65ca22dc2ef159c0abd696d","cross_cats_sorted":["cs.AI","cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-15T15:47:09Z","title_canon_sha256":"b07b213465e3ef7a1bce42aab6e5e21c85735096b3032eb34cea55c4180093c6"},"schema_version":"1.0","source":{"id":"2305.08732","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.08732","created_at":"2026-07-05T06:59:31Z"},{"alias_kind":"arxiv_version","alias_value":"2305.08732v3","created_at":"2026-07-05T06:59:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.08732","created_at":"2026-07-05T06:59:31Z"},{"alias_kind":"pith_short_12","alias_value":"IU65IOKQDM6K","created_at":"2026-07-05T06:59:31Z"},{"alias_kind":"pith_short_16","alias_value":"IU65IOKQDM6KVSKD","created_at":"2026-07-05T06:59:31Z"},{"alias_kind":"pith_short_8","alias_value":"IU65IOKQ","created_at":"2026-07-05T06:59:31Z"}],"graph_snapshots":[{"event_id":"sha256:4669768a354cd920c3714a7c6d670741835e94696cdb9d3a583a727fe76826a5","target":"graph","created_at":"2026-07-05T06:59:31Z","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/2305.08732/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Previous studies have revealed that vanilla pre-trained language models (PLMs) lack the capacity to handle knowledge-intensive NLP tasks alone; thus, several works have attempted to integrate external knowledge into PLMs. However, despite the promising outcome, we empirically observe that PLMs may have already encoded rich knowledge in their pre-trained parameters but fail to fully utilize them when applying them to knowledge-intensive tasks. In this paper, we propose a new paradigm dubbed Knowledge Rumination to help the pre-trained language model utilize that related latent knowledge without","authors_text":"Chuanqi Tan, Fei Huang, Huajun Chen, Ningyu Zhang, Peng Wang, Shengyu Mao, Yunzhi Yao","cross_cats":["cs.AI","cs.IR","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-15T15:47:09Z","title":"Knowledge Rumination for Pre-trained Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.08732","kind":"arxiv","version":3},"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:c0409326d8dafefe96ecc4b8f6f1970ffa7b78b275aac426d06c9c4b48d027ed","target":"record","created_at":"2026-07-05T06:59:31Z","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":"58800a61ba6e090238fb8fdf988d706206a6bc78b65ca22dc2ef159c0abd696d","cross_cats_sorted":["cs.AI","cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-15T15:47:09Z","title_canon_sha256":"b07b213465e3ef7a1bce42aab6e5e21c85735096b3032eb34cea55c4180093c6"},"schema_version":"1.0","source":{"id":"2305.08732","kind":"arxiv","version":3}},"canonical_sha256":"453dd439501b3caac9438a398a4a6e0179aa27b7048f484b9cfccad51ff8cae8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"453dd439501b3caac9438a398a4a6e0179aa27b7048f484b9cfccad51ff8cae8","first_computed_at":"2026-07-05T06:59:31.917929Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:59:31.917929Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s6b9xNKEYaRL3oxyzO4klRP9QsqBd6mtS50WuzOiLE+oMsBTRS0i0PVCNPueSOOyARrIf3XSKUO8L/lLHfK8AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:59:31.918413Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.08732","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0409326d8dafefe96ecc4b8f6f1970ffa7b78b275aac426d06c9c4b48d027ed","sha256:4669768a354cd920c3714a7c6d670741835e94696cdb9d3a583a727fe76826a5"],"state_sha256":"ee29c962cedf55ed418f5bd670a81477dc462e45901567599cf91cba2ed2f4c9"}