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Paper Citation Record · LEDGER

Constructing Large-Scale Real-World Benchmark Datasets for AIOps

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2208.03938.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2208.03938 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:34:13.846400Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T14:09:53.008856Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 19676c7d-2784-45ed-9471-1e904bddf1f2 · inbound

RCAEval: A Benchmark for Root Cause Analysis of Microservice Systems with Telemetry Data cites this paper.

RCAEval: A Benchmark for Root Cause Analysis of Microservice Systems with Telemetry Data Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T05:54:23.599731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:54:23.599731Z digest=sha256:5d44e17690476af39348e41924cf9071373c1299498de2e10ecf6166bfa0c15c

Observation c782d53c-1030-441d-a245-7b3de4034b58 · inbound

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models cites this paper.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T15:25:07.234948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:07.234948Z digest=sha256:006ac6dcf88f4d8b02547ecad66d1602d519dc03a0c8bf4db5c0846c60f5f876

Observation 85f3352b-a922-47ba-8239-9e7ced947c43 · inbound

Detecting Time Series Anomalies Like an Expert: A Multi-Agent LLM Framework with Specialized Analyzers cites this paper.

Detecting Time Series Anomalies Like an Expert: A Multi-Agent LLM Framework with Specialized Analyzers Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:31:09.988201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-08T11:43:28.398396Z digest=sha256:0d2c58af28848ed23e8d1b834d514a9b6ffd29a3013e14c21c5bfdd76a70be27

Observation 30d835bd-8720-4e94-856c-65b526657f88 · inbound

Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety cites this paper.

Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 127

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:57:53.827205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-14T19:54:21.290519Z digest=sha256:589c0f3fa0e8724c6b065f936398fb2d2367759bae8414d0445ad5b98341ac70

Observation a25ffa6d-f3c4-4d22-bc2f-8bcdc30fbd80 · inbound

Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety cites this paper.

Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 127

Resolution
verified exact
arxiv_id, observed 2026-06-30T22:05:06.015380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T21:57:42.035207Z digest=sha256:57ced61098a4905f599f10154ed9a0b558b8e8a7693f16f59b132381a04a4825

Observation a8ed2739-7e1a-4480-9546-a5f495af27ef · inbound

OpenRCA 2.0: From Outcome Labels to Causal Process Supervision cites this paper.

OpenRCA 2.0: From Outcome Labels to Causal Process Supervision Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:09:53.010508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T04:29:48.229226Z digest=sha256:2ee614bd01e69a14464a9cbdd8a81bf01964db3b7b25f0c155da7e4405562d83

Observation 9fcc92b4-7216-4af1-b0a4-609eca1e35b0 · inbound

OpenRCA 2.0: From Outcome Labels to Causal Process Supervision cites this paper.

OpenRCA 2.0: From Outcome Labels to Causal Process Supervision Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-01T07:05:28.207225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-07-01T07:05:01.491841Z digest=sha256:9ea5c3ec80b6968ec2c358f79bc153437b34c29aeac3ffa10c3c78bd7e39cf15

Observation be47d54a-f86d-45e5-947c-7a13bc8fd905 · inbound

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers cites this paper.

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-15T14:34:13.846400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:34:13.846400Z digest=sha256:2d51cf9f5a6c4a33ebec09dc8821c9f1cc26688a23077f900c26e1ee51c5f1e5