{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SDYECZQ4BIDFLYS3N4WU6HUICH","short_pith_number":"pith:SDYECZQ4","canonical_record":{"source":{"id":"2412.12522","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T04:22:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c93d49effc6049651f3e184df8a85a800ec1440b68705df9be916d71cc309461","abstract_canon_sha256":"9b3fed91dc6216065b19bcefe5e479041c9255ba2c150519653ade772a6d5f77"},"schema_version":"1.0"},"canonical_sha256":"90f041661c0a0655e25b6f2d4f1e8811fc5bd5552caef3d030f6ee6b90547b82","source":{"kind":"arxiv","id":"2412.12522","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.12522","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"arxiv_version","alias_value":"2412.12522v1","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.12522","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"pith_short_12","alias_value":"SDYECZQ4BIDF","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"pith_short_16","alias_value":"SDYECZQ4BIDFLYS3","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"pith_short_8","alias_value":"SDYECZQ4","created_at":"2026-07-05T09:50:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SDYECZQ4BIDFLYS3N4WU6HUICH","target":"record","payload":{"canonical_record":{"source":{"id":"2412.12522","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T04:22:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c93d49effc6049651f3e184df8a85a800ec1440b68705df9be916d71cc309461","abstract_canon_sha256":"9b3fed91dc6216065b19bcefe5e479041c9255ba2c150519653ade772a6d5f77"},"schema_version":"1.0"},"canonical_sha256":"90f041661c0a0655e25b6f2d4f1e8811fc5bd5552caef3d030f6ee6b90547b82","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:50:16.399307Z","signature_b64":"ipl0kHAaaGmcubVKLWATM7BadBjDYjuxfUBEqy0lckIyhXC71a/97Zz7A10rVsubQg2t4vxke+WPj6EkyYnGDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90f041661c0a0655e25b6f2d4f1e8811fc5bd5552caef3d030f6ee6b90547b82","last_reissued_at":"2026-07-05T09:50:16.398876Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:50:16.398876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.12522","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:50:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uJwG/hXA11bztuVvGP2RiHhf99Y3+LdjkbEYz+9r6WOfQywIgB8H+WJZU/YuknPwD6ejHGbQ9jxFbIP80LUACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T12:53:24.234523Z"},"content_sha256":"fd80c357bf1c68c9aa7c3cb712e475454c5c56390a78ce3f06b70e1b3420f6f6","schema_version":"1.0","event_id":"sha256:fd80c357bf1c68c9aa7c3cb712e475454c5c56390a78ce3f06b70e1b3420f6f6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SDYECZQ4BIDFLYS3N4WU6HUICH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Bo Hu, Geling Liu, Lingchen Zhao, Qian Wang, Ruichao Zhong, Yuanzhen Xie, Yunzhi Tan, Zang Li","submitted_at":"2024-12-17T04:22:22Z","abstract_excerpt":"Recently, large language models (LLMs) have significantly improved the performance of text-to-SQL systems. Nevertheless, many state-of-the-art (SOTA) approaches have overlooked the critical aspect of system robustness. Our experiments reveal that while LLM-driven methods excel on standard datasets, their accuracy is notably compromised when faced with adversarial perturbations. To address this challenge, we propose a robust text-to-SQL solution, called Solid-SQL, designed to integrate with various LLMs. We focus on the pre-processing stage, training a robust schema-linking model enhanced by LL"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.12522","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.12522/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:50:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fDr8Vnl0EryRI/RIYL4337UcEbaIAlqsycU0+x3+1Ylzr+ZqP6FVHxnZAoN36s54PIQg9GSvI7lEwshud2P8BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T12:53:24.235027Z"},"content_sha256":"893e0f24ba62edfb045c05189eb9ce31f5632d1fc1fb84b3e23c9c419e6d232a","schema_version":"1.0","event_id":"sha256:893e0f24ba62edfb045c05189eb9ce31f5632d1fc1fb84b3e23c9c419e6d232a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SDYECZQ4BIDFLYS3N4WU6HUICH/bundle.json","state_url":"https://pith.science/pith/SDYECZQ4BIDFLYS3N4WU6HUICH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SDYECZQ4BIDFLYS3N4WU6HUICH/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T12:53:24Z","links":{"resolver":"https://pith.science/pith/SDYECZQ4BIDFLYS3N4WU6HUICH","bundle":"https://pith.science/pith/SDYECZQ4BIDFLYS3N4WU6HUICH/bundle.json","state":"https://pith.science/pith/SDYECZQ4BIDFLYS3N4WU6HUICH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SDYECZQ4BIDFLYS3N4WU6HUICH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SDYECZQ4BIDFLYS3N4WU6HUICH","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":"9b3fed91dc6216065b19bcefe5e479041c9255ba2c150519653ade772a6d5f77","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T04:22:22Z","title_canon_sha256":"c93d49effc6049651f3e184df8a85a800ec1440b68705df9be916d71cc309461"},"schema_version":"1.0","source":{"id":"2412.12522","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.12522","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"arxiv_version","alias_value":"2412.12522v1","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.12522","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"pith_short_12","alias_value":"SDYECZQ4BIDF","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"pith_short_16","alias_value":"SDYECZQ4BIDFLYS3","created_at":"2026-07-05T09:50:16Z"},{"alias_kind":"pith_short_8","alias_value":"SDYECZQ4","created_at":"2026-07-05T09:50:16Z"}],"graph_snapshots":[{"event_id":"sha256:893e0f24ba62edfb045c05189eb9ce31f5632d1fc1fb84b3e23c9c419e6d232a","target":"graph","created_at":"2026-07-05T09:50:16Z","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/2412.12522/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, large language models (LLMs) have significantly improved the performance of text-to-SQL systems. Nevertheless, many state-of-the-art (SOTA) approaches have overlooked the critical aspect of system robustness. Our experiments reveal that while LLM-driven methods excel on standard datasets, their accuracy is notably compromised when faced with adversarial perturbations. To address this challenge, we propose a robust text-to-SQL solution, called Solid-SQL, designed to integrate with various LLMs. We focus on the pre-processing stage, training a robust schema-linking model enhanced by LL","authors_text":"Bo Hu, Geling Liu, Lingchen Zhao, Qian Wang, Ruichao Zhong, Yuanzhen Xie, Yunzhi Tan, Zang Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T04:22:22Z","title":"Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.12522","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:fd80c357bf1c68c9aa7c3cb712e475454c5c56390a78ce3f06b70e1b3420f6f6","target":"record","created_at":"2026-07-05T09:50:16Z","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":"9b3fed91dc6216065b19bcefe5e479041c9255ba2c150519653ade772a6d5f77","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T04:22:22Z","title_canon_sha256":"c93d49effc6049651f3e184df8a85a800ec1440b68705df9be916d71cc309461"},"schema_version":"1.0","source":{"id":"2412.12522","kind":"arxiv","version":1}},"canonical_sha256":"90f041661c0a0655e25b6f2d4f1e8811fc5bd5552caef3d030f6ee6b90547b82","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90f041661c0a0655e25b6f2d4f1e8811fc5bd5552caef3d030f6ee6b90547b82","first_computed_at":"2026-07-05T09:50:16.398876Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:50:16.398876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ipl0kHAaaGmcubVKLWATM7BadBjDYjuxfUBEqy0lckIyhXC71a/97Zz7A10rVsubQg2t4vxke+WPj6EkyYnGDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:50:16.399307Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.12522","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd80c357bf1c68c9aa7c3cb712e475454c5c56390a78ce3f06b70e1b3420f6f6","sha256:893e0f24ba62edfb045c05189eb9ce31f5632d1fc1fb84b3e23c9c419e6d232a"],"state_sha256":"9cdfdb2af13c3fa2c89895a4e9aebe832e6c24dca0178f5bcee5e202e3c20848"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pz+0icJ5BtdTJiDBufYrqMCoSBznObod5+lCYvkz+MzPqxjEeWQaXDYmF75RbY2V+7izlQHwjHMEmrxoarhcCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T12:53:24.238856Z","bundle_sha256":"9492c7b39a7d99613224aaae167e074e425e192396e40697019ffbab67544e2b"}}