{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OVBZXVVKDMHID5NZM7YU7C2I7S","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":"b8e27b208f1a638801918ab96d940c3d3d651dc21c6f7253fc64bfb9bfe62472","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-20T12:03:17Z","title_canon_sha256":"933ca28efbf9eff5e3c0ac1c7148a5381ffc55474fb7517088ffc0d0a6cfbadb"},"schema_version":"1.0","source":{"id":"2411.13244","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.13244","created_at":"2026-07-05T09:38:07Z"},{"alias_kind":"arxiv_version","alias_value":"2411.13244v1","created_at":"2026-07-05T09:38:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.13244","created_at":"2026-07-05T09:38:07Z"},{"alias_kind":"pith_short_12","alias_value":"OVBZXVVKDMHI","created_at":"2026-07-05T09:38:07Z"},{"alias_kind":"pith_short_16","alias_value":"OVBZXVVKDMHID5NZ","created_at":"2026-07-05T09:38:07Z"},{"alias_kind":"pith_short_8","alias_value":"OVBZXVVK","created_at":"2026-07-05T09:38:07Z"}],"graph_snapshots":[{"event_id":"sha256:8f19adcde1b13f695335db7c33d7d13a27cbd7f5dc602481cf8b66a1a6ddb578","target":"graph","created_at":"2026-07-05T09:38:07Z","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/2411.13244/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) exhibit impressive problem-solving skills across many tasks, but they still underperform compared to humans in various downstream applications, such as text-to-SQL. On the BIRD benchmark leaderboard, human performance achieves an accuracy of 92.96\\%, whereas the top-performing method reaches only 72.39\\%. Notably, these state-of-the-art (SoTA) methods predominantly rely on in-context learning to simulate human-like reasoning. However, they overlook a critical human skill: continual learning. Inspired by the educational practice of maintaining mistake notebooks duri","authors_text":"Qitao Qin, Zhibo Chu, Zichong Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-20T12:03:17Z","title":"Leveraging Prior Experience: An Expandable Auxiliary Knowledge Base for Text-to-SQL"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.13244","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":"sha256:080a63da02afdfed1424f035bdcac21c7360d4bbf6a80532c448bd6f9b418427","target":"record","created_at":"2026-07-05T09:38:07Z","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":"b8e27b208f1a638801918ab96d940c3d3d651dc21c6f7253fc64bfb9bfe62472","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-20T12:03:17Z","title_canon_sha256":"933ca28efbf9eff5e3c0ac1c7148a5381ffc55474fb7517088ffc0d0a6cfbadb"},"schema_version":"1.0","source":{"id":"2411.13244","kind":"arxiv","version":1}},"canonical_sha256":"75439bd6aa1b0e81f5b967f14f8b48fcb5c91aabd1dc57455fcd198bd3173629","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75439bd6aa1b0e81f5b967f14f8b48fcb5c91aabd1dc57455fcd198bd3173629","first_computed_at":"2026-07-05T09:38:07.288381Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:38:07.288381Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9X3Ch5E9o63os1NNb3w9tHjb2Xzm71n+2vskda2q8q7nj3wiDyqShN+jUaeTm7geaxfnawZxAZPnkFRCaf4uBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:38:07.288858Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.13244","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:080a63da02afdfed1424f035bdcac21c7360d4bbf6a80532c448bd6f9b418427","sha256:8f19adcde1b13f695335db7c33d7d13a27cbd7f5dc602481cf8b66a1a6ddb578"],"state_sha256":"22f08297d157401c7d97fe5cf996090a8f4a79cd8acdddfb9a8ebf0eb082a15a"}