{"as_of":"2026-08-09T08:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:54c3886f2affb785b63e512431b93c023ba891154c06ad46728305e03af724ea","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:57:28.748900Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":13,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.14834","snapshot_observed_at":"2026-08-07T00:57:28.748900Z","title":"Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.12320","last_updated":"2025-06-14T03:00:36Z","snapshot_observed_at":"2026-08-07T00:50:13.353326Z","submitted_at":"2025-06-14T03:00:36Z","title":"The Foundation Cracks: A Comprehensive Study on Bugs and Testing Practices in LLM Libraries","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:57:28.748900Z"},"links":{"cited_paper":"/paper/2212.14834","citing_paper":"/paper/2506.12320"},"observation_digest":"sha256:4ca45e03559717801601c5a6fd8e3efd71db916492596a010d8b9c401a668d1c","observation_id":"3cdbd95b-c5d3-416d-8498-8594cd2d7363","resolution":{"observed_at":"2026-08-07T00:57:28.748900Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.14834","snapshot_observed_at":"2026-08-06T16:24:29.910973Z","title":"Available: https://arxiv.org/abs/2212.14834","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.13629","last_updated":"2025-07-18T03:41:18Z","snapshot_observed_at":"2026-08-07T10:03:57.005879Z","submitted_at":"2025-07-18T03:41:18Z","title":"Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T16:24:29.910973Z"},"links":{"cited_paper":"/paper/2212.14834","citing_paper":"/paper/2507.13629"},"observation_digest":"sha256:63abb2b14021c7e7371d137c0d40fe1f129d4bdac7824f20b7372a8145b8e2e3","observation_id":"0bc14439-3f4b-42d1-b66e-463087c1f26d","resolution":{"observed_at":"2026-08-06T16:24:29.910973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models","version":4},"cited_work":{"arxiv_id":"2212.14834","doi":"10.48550/arxiv.2212.14834","metadata_source":"arxiv_reference","pith_arxiv_id":"2212.14834","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2212.14834 (2023).https://doi.org/10.48550/arXiv.2212.14834, accepted at ISSTA 2023","venue":"arXiv (Cornell University)","work_id":"251bcec8-9a99-4066-b060-99f975694f1a","year":2023},"citing_paper":{"arxiv_id":"2508.20340","last_updated":"2026-04-08T09:06:50Z","snapshot_observed_at":"2026-08-05T20:25:04.050714Z","submitted_at":"2025-08-28T01:21:26Z","title":"Once4All: Skeleton-Guided SMT Solver Fuzzing with LLM-Synthesized Generators","version":4},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-18T21:30:37.514348Z"},"links":{"cited_paper":"/paper/2212.14834","citing_paper":"/paper/2508.20340"},"observation_digest":"sha256:7ddad99b30560a2392f05101801bc99c35731887eb051af91fd6fa37ae419ecc","observation_id":"291bf0ee-6e08-4c11-9ec2-22f33d70681a","resolution":{"observed_at":"2026-05-18T21:31:51.293352Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models","version":4},"cited_work":{"arxiv_id":"2212.14834","doi":"10.48550/arxiv.2212.14834","metadata_source":"arxiv_reference","pith_arxiv_id":"2212.14834","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2212.14834 (2023).https://doi.org/10.48550/arXiv.2212.14834, accepted at ISSTA 2023","venue":"arXiv (Cornell University)","work_id":"251bcec8-9a99-4066-b060-99f975694f1a","year":2023},"citing_paper":{"arxiv_id":"2604.19905","last_updated":"2026-04-21T18:28:02Z","snapshot_observed_at":"2026-07-06T23:06:26.596990Z","submitted_at":"2026-04-21T18:28:02Z","title":"ViBR: Automated Bug Replay from Video-based Reports using Vision-Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-10T01:51:48.362249Z"},"links":{"cited_paper":"/paper/2212.14834","citing_paper":"/paper/2604.19905"},"observation_digest":"sha256:da6d25689219f81521701dd542f1bebb1622027c2be5eea9b2929af5e30504c2","observation_id":"33083ac4-a8bf-46dc-b92e-1ad0319054f7","resolution":{"observed_at":"2026-05-11T13:21:07.015791Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models","version":4},"cited_work":{"arxiv_id":"2212.14834","doi":"10.48550/arxiv.2212.14834","metadata_source":"arxiv_reference","pith_arxiv_id":"2212.14834","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2212.14834 (2023).https://doi.org/10.48550/arXiv.2212.14834, accepted at ISSTA 2023","venue":"arXiv (Cornell University)","work_id":"251bcec8-9a99-4066-b060-99f975694f1a","year":2023},"citing_paper":{"arxiv_id":"2606.26545","last_updated":"2026-06-25T02:43:48Z","snapshot_observed_at":"2026-08-08T09:19:58.129425Z","submitted_at":"2026-06-25T02:43:48Z","title":"ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-26T04:30:51.720496Z"},"links":{"cited_paper":"/paper/2212.14834","citing_paper":"/paper/2606.26545"},"observation_digest":"sha256:246a748b67761742f93ca5875414166ad560f6e7cd3cf0d0b9a9694f88623114","observation_id":"3bbac52f-aaab-490c-9069-65d59a8847c3","resolution":{"observed_at":"2026-06-26T05:09:00.780008Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.14834","snapshot_observed_at":"2026-08-01T07:12:18.071034Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.21530","last_updated":"2026-07-23T17:15:53Z","snapshot_observed_at":"2026-08-07T00:21:39.747357Z","submitted_at":"2026-07-23T17:15:53Z","title":"From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T07:12:18.071034Z"},"links":{"cited_paper":"/paper/2212.14834","citing_paper":"/paper/2607.21530"},"observation_digest":"sha256:fa7e2bad960f7a90f0edd4b6e26bf21047165f4521e1a2aa121f2a1462bd4337","observation_id":"6e8247db-cce2-46b3-b0ee-7df30300e8ea","resolution":{"observed_at":"2026-08-01T07:12:18.071034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2212.14834/citation-record","integrity":"/paper/2212.14834/integrity","json":"/paper/2212.14834/citation-record.json","paper":"/paper/2212.14834"},"outbound":[],"paper":{"arxiv_id":"2212.14834","last_updated":"2023-03-07T05:29:45Z","latest_version":4,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-05T08:52:23.753853Z","submitted_at":"2022-12-30T17:25:11Z","title":"Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2212.14834."}