{"as_of":"2026-08-10T04:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:de302c62baff51f92d78bc7cb08ef8f13707ad36a186fb03834a492c0fa48c1a","coverage":[{"denominator":8,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T15:04:48.289151Z","state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.18555/citation-record","integrity":"/paper/2607.18555/integrity","json":"/paper/2607.18555/citation-record.json","paper":"/paper/2607.18555"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T15:04:47.102054Z","title":"TestEra: A novel framework for automated testing of Java programs,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:47.102054Z"},"links":{"citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:a64d977a7342d79a47e1de413bb81f3830c9ad0598b30f4dd8f415032d592c8c","observation_id":"e05db58b-c203-4f8d-b5f9-717c151c63ad","resolution":{"observed_at":"2026-08-01T15:04:47.102054Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T15:04:47.292367Z","title":"Alloy: A lightweight object modelling notation,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:47.292367Z"},"links":{"citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:dee194fa1290d47e90988a8b70dfda0ed774ccc24d9e22b86664ad7cd8cd7bf2","observation_id":"52007df9-f027-4deb-8e6a-f4899114a629","resolution":{"observed_at":"2026-08-01T15:04:47.292367Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15441","last_updated":"2025-02-21T13:09:58Z","snapshot_observed_at":"2026-08-07T17:58:46.702093Z","submitted_at":"2025-02-21T13:09:58Z","title":"On the Effectiveness of Large Language Models in Writing Alloy Formulas","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15441","snapshot_observed_at":"2026-08-01T15:04:47.530935Z","title":"On the effectiveness of large language models in writing Alloy formulas,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:47.530935Z"},"links":{"cited_paper":"/paper/2502.15441","citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:7bb6047f89c13c70153e256b1e3eb2ea3c49054c775b2146fca0c092f3967cfb","observation_id":"6145b5e9-7705-4bb7-97e9-dfd90b5db7b0","resolution":{"observed_at":"2026-08-01T15:04:47.530935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.11050","last_updated":"2025-06-12T14:28:03Z","snapshot_observed_at":"2026-07-06T18:01:18.745347Z","submitted_at":"2024-04-17T03:46:38Z","title":"An Empirical Evaluation of Pre-trained Large Language Models for Repairing Declarative Formal Specifications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.11050","snapshot_observed_at":"2026-08-01T15:04:47.756227Z","title":"An empirical evaluation of pre-trained large language models for repairing declarative formal specifications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:47.756227Z"},"links":{"cited_paper":"/paper/2404.11050","citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:6424b0c17938eebcfb97ad3796cb7564131c255c1d1fa7047e1412e6faadd38d","observation_id":"15bd62c8-78b3-4372-9bda-af244d0625f2","resolution":{"observed_at":"2026-08-01T15:04:47.756227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T15:04:47.895365Z","title":"SpecGen: Automated generation of formal program specifications via large language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:47.895365Z"},"links":{"citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:93ba010ee868cacc3a8ef5b100bddd42a0bb21ff76efad73d3eb7c0084813765","observation_id":"5041ee1b-2cd3-4a44-a82e-1613f58dc3c5","resolution":{"observed_at":"2026-08-01T15:04:47.895365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.00044","last_updated":"2024-01-24T19:50:48Z","snapshot_observed_at":"2026-08-09T09:18:32.155230Z","submitted_at":"2023-09-29T18:00:01Z","title":"From particles to orbits: precise dark matter density profiles using dynamical information","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.00044","snapshot_observed_at":"2026-08-01T15:04:48.056132Z","title":"Leveraging large language models for auto- mated property generation in formal verification,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:48.056132Z"},"links":{"cited_paper":"/paper/2310.00044","citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:b9f8b8ed54836fc9fee9a074f6dbb69a66aa74765482e19483c90dab99119b9f","observation_id":"b7be9fab-ae52-44b3-aa72-df998d00f42c","resolution":{"observed_at":"2026-08-01T15:04:48.056132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T15:04:48.172400Z","title":"flipper-client: A lightweight, flexible library for feature flags in Python,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:48.172400Z"},"links":{"citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:a4fda161febd018d1ba8f275884fa9e533c0d87487201bd4923e797d8bcf18fc","observation_id":"f79877a3-25b2-4639-8a24-d0d77c128f3b","resolution":{"observed_at":"2026-08-01T15:04:48.172400Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T15:04:48.289151Z","title":"Cerberus: Data validation library for Python,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T15:04:48.289151Z"},"links":{"citing_paper":"/paper/2607.18555"},"observation_digest":"sha256:c82a6c50fa99f670c6a8bed35e6883c6263cea79bc779adc73ba5b812ee25a83","observation_id":"ac9b9c79-c0d9-4f5e-b6db-2a08acab09a7","resolution":{"observed_at":"2026-08-01T15:04:48.289151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.18555","last_updated":"2026-07-20T22:41:55Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-05T06:18:45.829784Z","submitted_at":"2026-07-20T22:41:55Z","title":"LM2Alloy: Investigating LLM-Generated Formal Specifications for Automated Test Derivation in Production Software"},"reference_resolution":{"displayed":8,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":8},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2607.18555."}