{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:3NOGSDW2T7FKW2IHYYFIDD4VYY","short_pith_number":"pith:3NOGSDW2","schema_version":"1.0","canonical_sha256":"db5c690eda9fcaab6907c60a818f95c6088ddf0b11035da248d8ed6c0ab3a70b","source":{"kind":"arxiv","id":"2605.17914","version":1},"attestation_state":"computed","paper":{"title":"Guiding LLM-based Loop Invariant Synthesis via Feedback on Local Reasoning Errors","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Junhao Liu, Peng Di, Tianchi Li, Xin Zhang, Zhenyu Yan","submitted_at":"2026-05-18T06:23:03Z","abstract_excerpt":"We propose a novel framework that provides constructive feedback to an LLM in the \"guess-and-check\" paradigm by formally verifying its own thinking process and detecting local reasoning errors. We apply this framework to the loop invariant synthesis problem. We prompt the model to produce a step-by-step natural language proof justifying its thinking process for the failed verification condition of its generated loop invariants. Then, we use an LLM to translate the reasoning steps into first-order logic implications, which can be checked automatically. An invalid implication pinpoints the exact"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.17914","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2026-05-18T06:23:03Z","cross_cats_sorted":[],"title_canon_sha256":"b407e54338fa6796096fcbb3afce5bd9132b4c57a8cb062ab333a63f8dab36bf","abstract_canon_sha256":"c4fd81aaab601e6548e7e25643ec658bb92d055f2d45558c17ae9fdb360872ef"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:05.664993Z","signature_b64":"5G2poTfBr5YNtdSFRN1BCY83Q184R0aYFeE0PXvdIDyqeursHU328nBZGTbfNFZM5H6ldwKuu9kTeSnnwhqrDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db5c690eda9fcaab6907c60a818f95c6088ddf0b11035da248d8ed6c0ab3a70b","last_reissued_at":"2026-05-20T00:05:05.664213Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:05.664213Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Guiding LLM-based Loop Invariant Synthesis via Feedback on Local Reasoning Errors","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Junhao Liu, Peng Di, Tianchi Li, Xin Zhang, Zhenyu Yan","submitted_at":"2026-05-18T06:23:03Z","abstract_excerpt":"We propose a novel framework that provides constructive feedback to an LLM in the \"guess-and-check\" paradigm by formally verifying its own thinking process and detecting local reasoning errors. We apply this framework to the loop invariant synthesis problem. We prompt the model to produce a step-by-step natural language proof justifying its thinking process for the failed verification condition of its generated loop invariants. Then, we use an LLM to translate the reasoning steps into first-order logic implications, which can be checked automatically. An invalid implication pinpoints the exact"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17914","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/2605.17914/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.17914","created_at":"2026-05-20T00:05:05.664345+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.17914v1","created_at":"2026-05-20T00:05:05.664345+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17914","created_at":"2026-05-20T00:05:05.664345+00:00"},{"alias_kind":"pith_short_12","alias_value":"3NOGSDW2T7FK","created_at":"2026-05-20T00:05:05.664345+00:00"},{"alias_kind":"pith_short_16","alias_value":"3NOGSDW2T7FKW2IH","created_at":"2026-05-20T00:05:05.664345+00:00"},{"alias_kind":"pith_short_8","alias_value":"3NOGSDW2","created_at":"2026-05-20T00:05:05.664345+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY","json":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY.json","graph_json":"https://pith.science/api/pith-number/3NOGSDW2T7FKW2IHYYFIDD4VYY/graph.json","events_json":"https://pith.science/api/pith-number/3NOGSDW2T7FKW2IHYYFIDD4VYY/events.json","paper":"https://pith.science/paper/3NOGSDW2"},"agent_actions":{"view_html":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY","download_json":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY.json","view_paper":"https://pith.science/paper/3NOGSDW2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.17914&json=true","fetch_graph":"https://pith.science/api/pith-number/3NOGSDW2T7FKW2IHYYFIDD4VYY/graph.json","fetch_events":"https://pith.science/api/pith-number/3NOGSDW2T7FKW2IHYYFIDD4VYY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY/action/storage_attestation","attest_author":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY/action/author_attestation","sign_citation":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY/action/citation_signature","submit_replication":"https://pith.science/pith/3NOGSDW2T7FKW2IHYYFIDD4VYY/action/replication_record"}},"created_at":"2026-05-20T00:05:05.664345+00:00","updated_at":"2026-05-20T00:05:05.664345+00:00"}