{"as_of":"2026-08-10T18:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e228ca3f8b72acdb4b33a9fa1c5e02b7502539bfb7b510df53d624898021c6f5","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":"2026-08-10T06:31:04.303077+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":"2026-08-09T12:32:14.663343Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-16T07:00:43.044725Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07610","snapshot_observed_at":"2026-08-09T12:32:14.663343Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02342","last_updated":"2025-02-04T14:20:51Z","snapshot_observed_at":"2026-08-10T01:05:04.415939Z","submitted_at":"2025-02-04T14:20:51Z","title":"SHIELD: APT Detection and Intelligent Explanation Using LLM","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T12:32:14.663343Z"},"links":{"cited_paper":"/paper/2308.07610","citing_paper":"/paper/2502.02342"},"observation_digest":"sha256:64ca961da2c7fa120744d6c6c6ec925e160844cc58d00e1cbbdb22fd2704f76e","observation_id":"55740275-5071-4f6e-8c75-0e3d3e047936","resolution":{"observed_at":"2026-08-09T12:32:14.663343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07610","snapshot_observed_at":"2026-08-03T08:15:24.140770Z","title":"Interpretable online log analysis using large language models with prompt strategies, 2024 d","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.17717","last_updated":"2026-06-09T20:25:14Z","snapshot_observed_at":"2026-08-08T23:34:38.789355Z","submitted_at":"2026-01-25T06:40:25Z","title":"A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data","version":3},"reference_index":134,"source":"arxiv_source","source_observed_at":"2026-08-03T08:15:24.140770Z"},"links":{"cited_paper":"/paper/2308.07610","citing_paper":"/paper/2601.17717"},"observation_digest":"sha256:6bc33b1c095056faa72f942e7736ef2dae7e88ffd9ac6468d2104f10155c695b","observation_id":"e1b2dbf4-30ba-4f81-8b00-6fa3332ecaae","resolution":{"observed_at":"2026-08-03T08:15:24.140770Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies","version":2},"cited_work":{"arxiv_id":"2308.07610","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.07610","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Interpretable online log analysis using large language models with prompt strategies","venue":null,"work_id":"b118852a-0963-4e63-8054-0a6b3c5a04fe","year":2024},"citing_paper":{"arxiv_id":"2602.07303","last_updated":"2026-04-17T15:29:54Z","snapshot_observed_at":"2026-08-03T09:54:39.877691Z","submitted_at":"2026-02-07T01:30:19Z","title":"KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-16T06:59:23.030671Z"},"links":{"cited_paper":"/paper/2308.07610","citing_paper":"/paper/2602.07303"},"observation_digest":"sha256:64721e3a01fd3410ff17e58aeec571af0eca792d71114078dad4d3b60c61b5ed","observation_id":"24b5d77d-a862-45b9-8b40-86e91489496a","resolution":{"observed_at":"2026-05-16T07:00:43.047167Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies","version":2},"cited_work":{"arxiv_id":"2308.07610","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.07610","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Interpretable online log analysis using large language models with prompt strategies","venue":null,"work_id":"b118852a-0963-4e63-8054-0a6b3c5a04fe","year":2024},"citing_paper":{"arxiv_id":"2604.12218","last_updated":"2026-04-14T02:51:48Z","snapshot_observed_at":"2026-07-06T23:00:28.036409Z","submitted_at":"2026-04-14T02:51:48Z","title":"LLM-Enhanced Log Anomaly Detection: A Comprehensive Benchmark of Large Language Models for Automated System Diagnostics","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T15:40:52.336041Z"},"links":{"cited_paper":"/paper/2308.07610","citing_paper":"/paper/2604.12218"},"observation_digest":"sha256:814bb1182b5b17f302c4bd7190d1251f13f13ec5a5d242d30090725e4b16b7d4","observation_id":"e2b665bd-281a-4dcb-bcec-5c2175366f02","resolution":{"observed_at":"2026-05-11T10:01:03.815364Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies","version":2},"cited_work":{"arxiv_id":"2308.07610","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.07610","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Interpretable online log analysis using large language models with prompt strategies","venue":null,"work_id":"b118852a-0963-4e63-8054-0a6b3c5a04fe","year":2024},"citing_paper":{"arxiv_id":"2604.22819","last_updated":"2026-04-16T13:04:52Z","snapshot_observed_at":"2026-07-06T23:09:10.050398Z","submitted_at":"2026-04-16T13:04:52Z","title":"A pragmatic approach to regulating AI agents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T10:00:09.382458Z"},"links":{"cited_paper":"/paper/2308.07610","citing_paper":"/paper/2604.22819"},"observation_digest":"sha256:a639be03594dacde9a935db2418a7a1848cad41dd24afa40947b4e789f340461","observation_id":"5c750549-8c70-424f-b687-e35c5f387957","resolution":{"observed_at":"2026-05-10T10:04:06.870715Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies","version":2},"cited_work":{"arxiv_id":"2308.07610","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.07610","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Interpretable online log analysis using large language models with prompt strategies","venue":null,"work_id":"b118852a-0963-4e63-8054-0a6b3c5a04fe","year":2024},"citing_paper":{"arxiv_id":"2605.08316","last_updated":"2026-05-08T14:58:52Z","snapshot_observed_at":"2026-08-04T08:55:54.382325Z","submitted_at":"2026-05-08T14:58:52Z","title":"AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey","version":1},"reference_index":161,"source":"pdf_text","source_observed_at":"2026-05-12T00:50:39.655353Z"},"links":{"cited_paper":"/paper/2308.07610","citing_paper":"/paper/2605.08316"},"observation_digest":"sha256:0b5b7c82269986704edd241ae7de8f127620deb49dc2193b8bee938890b3c025","observation_id":"0bfcae61-a0f1-48be-934d-c106e3d8b4d3","resolution":{"observed_at":"2026-05-12T00:51:14.714983Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2308.07610/citation-record","integrity":"/paper/2308.07610/integrity","json":"/paper/2308.07610/citation-record.json","paper":"/paper/2308.07610"},"outbound":[],"paper":{"arxiv_id":"2308.07610","last_updated":"2024-01-26T02:46:11Z","latest_version":2,"primary_category":"cs.SE","snapshot_observed_at":"2026-07-06T16:06:18.758673Z","submitted_at":"2023-08-15T07:40:21Z","title":"Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2308.07610."}