{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:FE55MM4RSLDNRKM6V6I3J6DOVR","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":"113e9a15a8877122fdc95b9951015e42001e7dc3528f101010456a5ea84a353c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T15:07:35Z","title_canon_sha256":"b359083f3bd5921308a911f702ddfa6f02fb2b0d62ef815fe2d1660c11576b5c"},"schema_version":"1.0","source":{"id":"2602.12996","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.12996","created_at":"2026-06-09T01:05:14Z"},{"alias_kind":"arxiv_version","alias_value":"2602.12996v2","created_at":"2026-06-09T01:05:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.12996","created_at":"2026-06-09T01:05:14Z"},{"alias_kind":"pith_short_12","alias_value":"FE55MM4RSLDN","created_at":"2026-06-09T01:05:14Z"},{"alias_kind":"pith_short_16","alias_value":"FE55MM4RSLDNRKM6","created_at":"2026-06-09T01:05:14Z"},{"alias_kind":"pith_short_8","alias_value":"FE55MM4R","created_at":"2026-06-09T01:05:14Z"}],"graph_snapshots":[{"event_id":"sha256:7522ac82353e1448db60336d701a991c6b7270717bb1fa74cd113c1437e4af1f","target":"graph","created_at":"2026-06-09T01:05:14Z","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/2602.12996/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge augmentation has significantly enhanced the performance of Large Language Models (LLMs) in knowledge-intensive tasks. However, existing methods typically operate on the simplistic premise that model performance equates with internal knowledge, overlooking the knowledge-confidence gaps that lead to overconfident errors or uncertain truths. To bridge this gap, we propose a novel meta-cognitive framework for reliable knowledge augmentation via differentiated intervention and alignment. Our approach leverages internal cognitive signals to partition the knowledge space into mastered, conf","authors_text":"Hao Chen, Maosong Sun, Qingfu Zhu, Wanxiang Che, Ye He, Yuchun Fan, Yukun Yan, Zhenghao Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T15:07:35Z","title":"Know More, Know Clearer: A Meta-Cognitive Framework for Knowledge Augmentation in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.12996","kind":"arxiv","version":2},"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":"sha256:809a1e9420e4589f1bd96dcde576275af196818d272317455a0605e79e6170a8","target":"record","created_at":"2026-06-09T01:05:14Z","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":"113e9a15a8877122fdc95b9951015e42001e7dc3528f101010456a5ea84a353c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T15:07:35Z","title_canon_sha256":"b359083f3bd5921308a911f702ddfa6f02fb2b0d62ef815fe2d1660c11576b5c"},"schema_version":"1.0","source":{"id":"2602.12996","kind":"arxiv","version":2}},"canonical_sha256":"293bd6339192c6d8a99eaf91b4f86eac51b160377ee5e049ec72ae53a8eedf38","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"293bd6339192c6d8a99eaf91b4f86eac51b160377ee5e049ec72ae53a8eedf38","first_computed_at":"2026-06-09T01:05:14.343068Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T01:05:14.343068Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7egyPx6qDfsl8KOktAn9fnoXQZCnVbX33gN4Fr928X/40DQSVqJNw9O3SdYTvMy01fRU+s0dL+Daa/in0VMCDA==","signature_status":"signed_v1","signed_at":"2026-06-09T01:05:14.343604Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.12996","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:809a1e9420e4589f1bd96dcde576275af196818d272317455a0605e79e6170a8","sha256:7522ac82353e1448db60336d701a991c6b7270717bb1fa74cd113c1437e4af1f"],"state_sha256":"5fd6dc9756e1eac7f64f6f8962b1310515300b128172f96404b2b626fdace1f5"}