{"as_of":"2026-08-09T19:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:38c5e5a3272e9f9f34b4e516fcf5af38450e7c3595fcdcd9b71c5bdd4472395b","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:23:41.521031Z","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":"2026-06-30T02:44:11.435811Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-08-07T00:23:41.521031Z","title":"Opseval: A compre- hensive task-oriented aiops benchmark for large language models.arXiv preprint arXiv:2310.07637, 2023","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14336","last_updated":"2025-06-17T09:20:09Z","snapshot_observed_at":"2026-08-09T06:07:34.749286Z","submitted_at":"2025-06-17T09:20:09Z","title":"AviationLLM: An LLM-based Knowledge System for Aviation Training","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:41.521031Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2506.14336"},"observation_digest":"sha256:90298d615467cfae1669c601d4105128b9c8221adf5fc6e9754f8dd721a9d1d3","observation_id":"fbf3bf20-535a-4935-a195-81c8c45d179d","resolution":{"observed_at":"2026-08-07T00:23:41.521031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-08-06T18:08:49.556866Z","title":"Opseval: A comprehensive benchmark suite for evaluating large language models’ capability in the IT operations domain","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09063","last_updated":"2025-07-11T22:45:07Z","snapshot_observed_at":"2026-08-08T09:04:57.537928Z","submitted_at":"2025-07-11T22:45:07Z","title":"SetupBench: Assessing Software Engineering Agents' Ability to Bootstrap Development Environments","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T18:08:49.556866Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2507.09063"},"observation_digest":"sha256:b8159a64be6a57ffbd38e6ba17fcef5b3e7693ede6099350243529125636e011","observation_id":"465e73db-8c85-484f-bde7-400bdb029460","resolution":{"observed_at":"2026-08-06T18:08:49.556866Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-08-06T23:26:36.786910Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12472","last_updated":"2025-06-23T02:40:16Z","snapshot_observed_at":"2026-08-08T12:19:02.219120Z","submitted_at":"2025-06-23T02:40:16Z","title":"A Survey of AIOps in the Era of Large Language Models","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T23:26:36.786910Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2507.12472"},"observation_digest":"sha256:bd6e92b59e9f8a225ed9a3a0deca8382f2cbcfc188f7c9b84c775afb0c947a4e","observation_id":"76625ad5-70ef-414b-8d62-6c69d81a27d5","resolution":{"observed_at":"2026-08-06T23:26:36.786910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":"2310.07637","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-06-30T02:44:11.435811Z","title":null,"venue":null,"work_id":"a7a8c794-4960-4c4c-a1c8-f9b185752f6e","year":2023},"citing_paper":{"arxiv_id":"2605.02906","last_updated":"2026-07-31T03:14:41Z","snapshot_observed_at":"2026-08-05T23:10:40.522491Z","submitted_at":"2026-04-06T02:40:18Z","title":"OpsLLM: Construction of Large Language Model for Software Operations with Multi-stage Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-10T20:07:07.548384Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2605.02906"},"observation_digest":"sha256:85cb8b4e51babc6e41066eba6ec4a7f6b95be46449c638d22ab0c7960e43ceed","observation_id":"74b96254-2e39-448f-bc73-9b2fa00af62c","resolution":{"observed_at":"2026-05-10T22:15:48.651505Z","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":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":"2310.07637","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-06-30T02:44:11.435811Z","title":null,"venue":null,"work_id":"a7a8c794-4960-4c4c-a1c8-f9b185752f6e","year":2023},"citing_paper":{"arxiv_id":"2605.02906","last_updated":"2026-07-31T03:14:41Z","snapshot_observed_at":"2026-08-05T23:10:40.522491Z","submitted_at":"2026-04-06T02:40:18Z","title":"OpsLLM: Construction of Large Language Model for Software Operations with Multi-stage Learning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-13T06:25:16.650306Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2605.02906"},"observation_digest":"sha256:b5d92cf8971932d012c8d22fbd766c17a1339f2a47e1104c9beca40db53db24d","observation_id":"5ecd2eb1-32b2-46ec-b394-5275af059bd7","resolution":{"observed_at":"2026-05-13T06:27:24.625532Z","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":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-08-03T02:30:33.221329Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2605.02906","last_updated":"2026-07-31T03:14:41Z","snapshot_observed_at":"2026-08-05T23:10:40.522491Z","submitted_at":"2026-04-06T02:40:18Z","title":"OpsLLM: Construction of Large Language Model for Software Operations with Multi-stage Learning","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T02:30:33.221329Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2605.02906"},"observation_digest":"sha256:b67382e9b63e842c2bc15f166de602f6489a0bfd657cb1aeb45d497891ea7db6","observation_id":"61b04163-e2b6-48f3-82ab-7f157bc6ba8e","resolution":{"observed_at":"2026-08-03T02:30:33.221329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":"2310.07637","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-06-30T02:44:11.435811Z","title":null,"venue":null,"work_id":"a7a8c794-4960-4c4c-a1c8-f9b185752f6e","year":2023},"citing_paper":{"arxiv_id":"2605.07161","last_updated":"2026-07-30T18:34:51Z","snapshot_observed_at":"2026-08-05T23:10:40.907300Z","submitted_at":"2026-05-08T02:47:07Z","title":"SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarios","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-11T02:20:32.528550Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2605.07161"},"observation_digest":"sha256:b91ec99dba2c3b3fb5df75d58a0d503eafcc5a9007db9dc30121f77fbc62933f","observation_id":"4627ea89-cb98-4615-8fe5-83ce38880188","resolution":{"observed_at":"2026-05-11T02:20:54.800888Z","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":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":"2310.07637","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-06-30T02:44:11.435811Z","title":null,"venue":null,"work_id":"a7a8c794-4960-4c4c-a1c8-f9b185752f6e","year":2023},"citing_paper":{"arxiv_id":"2605.07161","last_updated":"2026-07-30T18:34:51Z","snapshot_observed_at":"2026-08-05T23:10:40.907300Z","submitted_at":"2026-05-08T02:47:07Z","title":"SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarios","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-14T21:49:16.239350Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2605.07161"},"observation_digest":"sha256:64395f63dbe2fe6449f0d75ef3a07c1eea5e9bd92217dd5e92f922060fe800b2","observation_id":"415face9-d8af-4ef5-8965-40edc8f485c1","resolution":{"observed_at":"2026-05-14T21:49:29.215706Z","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":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-08-03T00:18:42.347258Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.07161","last_updated":"2026-07-30T18:34:51Z","snapshot_observed_at":"2026-08-05T23:10:40.907300Z","submitted_at":"2026-05-08T02:47:07Z","title":"SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarios","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T00:18:42.347258Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2605.07161"},"observation_digest":"sha256:00073deeb4eb31dd6c10bbfd7b88ecc1bee2d5f25daa5141ef198070861539e3","observation_id":"c3cc156d-7930-491c-8130-d71444712d21","resolution":{"observed_at":"2026-08-03T00:18:42.347258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":"2310.07637","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-06-30T02:44:11.435811Z","title":null,"venue":null,"work_id":"a7a8c794-4960-4c4c-a1c8-f9b185752f6e","year":2023},"citing_paper":{"arxiv_id":"2606.29193","last_updated":"2026-06-28T04:38:05Z","snapshot_observed_at":"2026-08-07T11:31:06.401704Z","submitted_at":"2026-06-28T04:38:05Z","title":"A Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure Diagnosis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-30T02:43:30.037342Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2606.29193"},"observation_digest":"sha256:9cf3847ae631baceb96180967d8b1e4cd8356f1d6b4c18e6f53039128199b81f","observation_id":"dd1f44f0-cf79-43ab-b804-2cbbd711591a","resolution":{"observed_at":"2026-06-30T02:44:11.437652Z","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":"2310.07637","last_updated":"2025-06-17T12:53:20Z","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07637","snapshot_observed_at":"2026-08-01T05:37:52.821305Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22165","last_updated":"2026-07-24T10:11:24Z","snapshot_observed_at":"2026-08-06T13:21:04.844092Z","submitted_at":"2026-07-24T10:11:24Z","title":"DBA-Bench: A Production-Fidelity Benchmark for LLM-Based Database Operations Agents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T05:37:52.821305Z"},"links":{"cited_paper":"/paper/2310.07637","citing_paper":"/paper/2607.22165"},"observation_digest":"sha256:d198610b1ee663d2044a665bbc82d69950fd773d025bd93a06ce89cf9cab0a96","observation_id":"8e90c3c3-167d-410d-9275-2cab651b3349","resolution":{"observed_at":"2026-08-01T05:37:52.821305Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2310.07637/citation-record","integrity":"/paper/2310.07637/integrity","json":"/paper/2310.07637/citation-record.json","paper":"/paper/2310.07637"},"outbound":[],"paper":{"arxiv_id":"2310.07637","last_updated":"2025-06-17T12:53:20Z","latest_version":5,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T16:31:21.196640Z","submitted_at":"2023-10-11T16:33:29Z","title":"OpsEval: A Comprehensive IT Operations Benchmark Suite for 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 11 inbound Pith citation observations for arXiv:2310.07637."}