Paper Citation Record · LEDGER

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

As of 18 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 8 inbound Pith citation observations for arXiv:2501.14170.

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

pith.paper-citation-record.v1
2501.14170 v1

Coverage vector

measured 96 of 96 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:25:07.515819Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:12:26.571229Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T12:23:24.656301Z

Reference resolution

96 of 96 outbound references displayed

verified exact1
verified fuzzy46
unresolved49
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2a20f352-28c9-4f4f-b336-380f84724710 · outbound

This paper cites GPT-4 Technical Report.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bf98996-4118-432e-aa15-692b0ecd7038 · outbound

This paper cites Recommending root-cause and mitigation steps for cloud incidents using large language models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Recommending root-cause and mitigation steps for cloud incidents using large language models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.097233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a16ed257-d1a7-4ecc-861c-1ededaa6a0bc · outbound

This paper cites Sintel: A machine learning framework to extract insights from signals.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Sintel: A machine learning framework to extract insights from signals

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.102196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c403a3d-59f8-40eb-b44e-ab7cb4f90dee · outbound

This paper cites Large language models can be zero-shot anomaly detectors for time series?.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Large language models can be zero-shot anomaly detectors for time series?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.106568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9b9aedc-1603-49c4-a4e5-2b134473c95d · outbound

This paper cites Performance analysis of cloud applications.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Performance analysis of cloud applications

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.111298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feb81d62-1d22-4a89-b295-30f06e078833 · outbound

This paper cites Language Models are Few-Shot Learners.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Language Models are Few-Shot Learners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.115682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd0cc686-c3ab-4c4d-ad88-68b369109738 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Evaluating Large Language Models Trained on Code

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.120864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef76fb98-30a2-4bb9-b4e7-67ab31da8783 · outbound

This paper cites Automatic root cause analysis via large language models for cloud in- cidents.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Automatic root cause analysis via large language models for cloud in- cidents

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.125422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4fe7a0a-46a2-4000-8b21-0027f97b75f5 · outbound

This paper cites AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.129425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7036d577-a8ae-4cc1-a1fc-a52b005867a5 · outbound

This paper cites Automated anomaly detection and performance modeling of enterprise appli- cations.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Automated anomaly detection and performance modeling of enterprise appli- cations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.133788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68bf98fc-0d05-451d-9878-05d562196dc5 · outbound

This paper cites ServiceLab: Preventing tiny performance regressions at hyperscale through Pre-Production test- ing.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models ServiceLab: Preventing tiny performance regressions at hyperscale through Pre-Production test- ing

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.137993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4be05dce-f21e-4ff5-8bb4-45cdc8901499 · outbound

This paper cites Large language models are zero-shot fuzzers: Fuzzing deep-learning li- braries via large language models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Large language models are zero-shot fuzzers: Fuzzing deep-learning li- braries via large language models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.142007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd68b646-fee8-43ee-9f85-b28b3da4b266 · outbound

This paper cites Can LLMs Serve As Time Series Anomaly Detectors?.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Can LLMs Serve As Time Series Anomaly Detectors?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.146038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a126f64-11fc-4175-b742-17784f4fc488 · outbound

This paper cites The Llama 3 Herd of Models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.150074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58599e16-c470-4e71-8005-558032cb3a7a · outbound

This paper cites Early ex- ploration of using chatgpt for log-based anomaly detec- tion on parallel file systems logs.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Early ex- ploration of using chatgpt for log-based anomaly detec- tion on parallel file systems logs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.153861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f18e1398-ec40-4290-a79c-8f1745351ec0 · outbound

This paper cites An evaluation of anomaly detection and diagnosis in multivariate time series.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models An evaluation of anomaly detection and diagnosis in multivariate time series

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.157964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cad071c6-3e39-48cc-8d57-0882ed4daec1 · outbound

This paper cites X-lifecycle learning for cloud incident management using llms.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models X-lifecycle learning for cloud incident management using llms

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.161839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff0b931f-78a6-49c7-bdc2-63f6f420aecc · outbound

This paper cites Large language models are zero-shot time series forecasters.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Large language models are zero-shot time series forecasters

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.165871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8062eb84-79c5-48f7-bc2b-0c33b9931c91 · outbound

This paper cites Acto: Automatic end-to-end testing for operation correctness of cloud system management.Pro- ceedings of the 29th Symposium on Operating Systems Principles, 2023.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Acto: Automatic end-to-end testing for operation correctness of cloud system management.Pro- ceedings of the 29th Symposium on Operating Systems Principles, 2023

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.170424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3b5a068-06bb-4fd6-8e99-8b3af13bde79 · outbound

This paper cites Logllm: Log-based anomaly detection using large lan- guage models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Logllm: Log-based anomaly detection using large lan- guage models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.174844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e0a39b9-1d79-48cd-88f3-0bcebe2b0ad4 · outbound

This paper cites Auto- mated reasoning and detection of specious configura- tion in large systems with symbolic execution.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Auto- mated reasoning and detection of specious configura- tion in large systems with symbolic execution

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.179136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26507680-90d2-4b10-b850-2b53285e2ba6 · outbound

This paper cites GPT-4o System Card.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models GPT-4o System Card

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.183601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b34274cb-2526-4586-84b5-18577995a700 · outbound

This paper cites Xpert: Empowering inci- dent management with query recommendations via large language models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Xpert: Empowering inci- dent management with query recommendations via large language models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.188104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fab38c7-2b90-48d4-b875-6715128164bc · outbound

This paper cites MegaScale: Scaling large language model training to more than 10,000 GPUs.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models MegaScale: Scaling large language model training to more than 10,000 GPUs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.192398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 261708dc-cc3f-421f-acfa-4d18897cf52a · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.196821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ff58227-969d-4077-b1de-cb10447850c8 · outbound

This paper cites Towards a rigorous evaluation of time-series anomaly detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Towards a rigorous evaluation of time-series anomaly detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.800322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d79c372d-8aaf-4db0-9347-11739ee78519 · outbound

This paper cites A benchmark dataset for time series anomaly detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models A benchmark dataset for time series anomaly detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.785843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0779d3aa-91a9-4da4-93b8-3f563ff02d03 · outbound

This paper cites Generic and scalable framework for automated time-series anomaly detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Generic and scalable framework for automated time-series anomaly detection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.771376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4c7c8daa-8bcd-4bee-a38e-3829d6aa9085 · outbound

This paper cites Log-based anomaly detection without log parsing.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Log-based anomaly detection without log parsing

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.756867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ceb85df-ab13-4084-8962-07913e5eb445 · outbound

This paper cites Efficient backprop.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Efficient backprop

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.742124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3770af0c-c792-4047-8f81-5f385a73bc58 · outbound

This paper cites Predictive and adap- tive failure mitigation to avert production cloud VM in- terruptions.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Predictive and adap- tive failure mitigation to avert production cloud VM in- terruptions

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.728265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation afcde93a-346b-4101-b134-4f19f1409a80 · outbound

This paper cites Gandalf: An intelligent, End-To-End analytics service for safe deployment in Large-Scale cloud infrastructure.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Gandalf: An intelligent, End-To-End analytics service for safe deployment in Large-Scale cloud infrastructure

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.713981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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

This paper cites Constructing Large-Scale Real-World Benchmark Datasets for AIOps.

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

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Observation 9e8bc141-d52f-469f-b516-bd5ac329e414 · outbound

This paper cites A survey on explainable anomaly detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models A survey on explainable anomaly detection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.700632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9953e368-fb0c-4a4b-ba5d-3ff2b53da1c1 · outbound

This paper cites Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.244235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6909540f-bd14-4f52-a105-74b6d85b124d · outbound

This paper cites Logprompt: Prompt engi- neering towards zero-shot and interpretable log analysis.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Logprompt: Prompt engi- neering towards zero-shot and interpretable log analysis

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.685917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1344b4f8-6459-444d-94aa-5ce27ad3ca6b · outbound

This paper cites RESIN: A holistic service for dealing with memory leaks in production cloud infrastructure.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models RESIN: A holistic service for dealing with memory leaks in production cloud infrastructure

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.672100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6d5047be-e47e-40c8-8959-08ee9a504362 · outbound

This paper cites Long short term memory networks for anomaly detection in time series.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Long short term memory networks for anomaly detection in time series

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.658544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7a6fb470-a969-4b5b-992f-860e9e3addbb · outbound

This paper cites Azure openai service models - azure ope- nai.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Azure openai service models - azure ope- nai

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.644303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d0a7607d-e842-44c5-a2ee-63b8b57b0722 · outbound

This paper cites Azure openai service – advanced lan- guage models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Azure openai service – advanced lan- guage models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.630238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a37b8ca4-43da-4d1f-804a-d6bdb78ccdf8 · outbound

This paper cites Dasv4 size series - azure virtual machines.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Dasv4 size series - azure virtual machines

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.615881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c3810f01-7261-44c3-a9ce-b5350b80e21d · outbound

This paper cites Ndm_a100_v4 sizes series - azure vir- tual machines.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Ndm_a100_v4 sizes series - azure vir- tual machines

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.601389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 077de084-1619-4ae7-8452-503e6f96fe03 · outbound

This paper cites Investigating the Limitations of Transformers with Simple Arithmetic Tasks.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Investigating the Limitations of Transformers with Simple Arithmetic Tasks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.277129Z

Source-reported events for the cited work

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Observation f7218be8-359b-43bc-a1aa-3689218be3bf · outbound

This paper cites How to detect which node causes a nccl hang.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models How to detect which node causes a nccl hang

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.587282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 510a1495-6268-4d03-bab4-0cbad3e429dd · outbound

This paper cites An empirical study of the non-determinism of chatgpt in code generation.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models An empirical study of the non-determinism of chatgpt in code generation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.558673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 41ecf2b6-9408-453a-b169-651d8b391a39 · outbound

This paper cites Toward explain- able deep anomaly detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Toward explain- able deep anomaly detection

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.543596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1535f5c1-f671-4be9-9d77-05cc8f20c743 · outbound

This paper cites Lag-llama: Towards foundation models for time series forecasting.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Lag-llama: Towards foundation models for time series forecasting

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.528574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2893884a-86a4-41f1-a193-a36b813c9a71 · outbound

This paper cites AIOps Solutions for Incident Management: Technical Guidelines and A Comprehensive Literature Review.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models AIOps Solutions for Incident Management: Technical Guidelines and A Comprehensive Literature Review

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.301112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b8d7fbb-8936-45c4-9a14-0ee6bd2193a7 · outbound

This paper cites Time-series anomaly detection service at microsoft.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Time-series anomaly detection service at microsoft

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.514047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 77a1c203-3e93-4aa6-826a-1505d69d969b · outbound

This paper cites A stochastic ap- proximation method.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models A stochastic ap- proximation method

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.499802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4a5d1c77-816c-4286-a2a0-df350038494d · outbound

This paper cites Rousseeuw and A.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Rousseeuw and A

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.484763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8c96248d-c1c2-4981-82f6-23b1f16a94ce · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Code Llama: Open Foundation Models for Code

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.317164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00ca6488-eaee-4baf-b95e-ddd7e8804fb6 · outbound

This paper cites Deep one-class classification.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Deep one-class classification

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.469586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 91d8fc30-b399-46ce-b74c-4e815a063c31 · outbound

This paper cites Summary of the aws ser- vice event in the northern virginia (us-east-1) region.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Summary of the aws ser- vice event in the northern virginia (us-east-1) region

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.455409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d8c4ac0c-5d09-45e6-857e-0702b6b6555c · outbound

This paper cites TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models

Reference 55

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:25:07.647885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 87ad97f7-0226-403e-9159-7dbbbaab4964 · outbound

This paper cites Anomaly detection in streams with extreme value theory.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Anomaly detection in streams with extreme value theory

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.441122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6f0581e5-b9cb-4632-9c5b-85620df85465 · outbound

This paper cites The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.338958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53882791-e175-4902-9a39-d3c5714589d5 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.426211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3edab011-1bd0-42ef-9596-45b20021b630 · outbound

This paper cites TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.348377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1962d22-cc70-4914-81d5-4f470acf4bad · outbound

This paper cites Large- scale cluster management at google with borg.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Large- scale cluster management at google with borg

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.410928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe0f70fe-2bb5-4080-be4c-b609f706c9f7 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.357424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ed55c10-7d7c-47a2-8319-63734d002a93 · outbound

This paper cites Rcagent: Cloud root cause anal- ysis by autonomous agents with tool-augmented large language models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Rcagent: Cloud root cause anal- ysis by autonomous agents with tool-augmented large language models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.362039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eaddd19-061f-42ff-a37d-5b60c1444831 · outbound

This paper cites Revisiting vae for unsupervised time series anomaly detection: A fre- quency perspective.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Revisiting vae for unsupervised time series anomaly detection: A fre- quency perspective

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.385323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c43b714e-a6b8-49f2-9760-abf094979884 · outbound

This paper cites Effective performance issue diagno- sis with value-assisted cost profiling.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Effective performance issue diagno- sis with value-assisted cost profiling

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.370346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 78dbd7ba-42cd-40d3-8508-4011843e8a6a · outbound

This paper cites Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.381003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feb71b89-9efb-43bb-a9cb-95e992806f05 · outbound

This paper cites SuperBench: Improving cloud AI infrastructure reliability with proactive valida- tion.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models SuperBench: Improving cloud AI infrastructure reliability with proactive valida- tion

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.345448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 89bba234-4220-4025-bff3-246da7a53f3e · outbound

This paper cites Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web appli- cations.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web appli- cations

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.330569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94423b0b-ca0e-492e-a545-d4bde31acf8a · outbound

This paper cites Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.394187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d9c923b-650f-4a18-b458-4a9aa524393d · outbound

This paper cites Fbdetect: Catching tiny performance regressions at hyperscale through in-production moni- toring.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Fbdetect: Catching tiny performance regressions at hyperscale through in-production moni- toring

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.315722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1f70d549-2046-436a-b40d-c7e2650d83f9 · outbound

This paper cites Tfad: A decomposition time series anomaly de- tection architecture with time-frequency analysis.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Tfad: A decomposition time series anomaly de- tection architecture with time-frequency analysis

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.300583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 50da574c-1bbe-4add-b253-6c2359e6ad35 · outbound

This paper cites Mishra, Tri Tran, Minghua Ma, Qing- wei Lin, Murali Chintalapati, and Dongmei Zhang.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Mishra, Tri Tran, Minghua Ma, Qing- wei Lin, Murali Chintalapati, and Dongmei Zhang

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.286469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ec85d19f-f0cf-46f6-82e3-1021d18b5f5e · outbound

This paper cites A Survey of AIOps for Failure Management in the Era of Large Language Models.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models A Survey of AIOps for Failure Management in the Era of Large Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.410173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97007e25-a4ce-4dfc-88ec-ce6f8737f4a3 · outbound

This paper cites Automated root causing of cloud incidents using in- context learning with gpt-4.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Automated root causing of cloud incidents using in- context learning with gpt-4

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.272358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9331d958-eae5-4d95-8a24-c2e5608f4189 · outbound

This paper cites Towards reproducible, automated, and scal- able anomaly detection.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Towards reproducible, automated, and scal- able anomaly detection

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.258474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a2d9160f-aef1-48e3-b5ce-59e6fedddf2c · outbound

This paper cites In- former: Beyond efficient transformer for long sequence time-series forecasting.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models In- former: Beyond efficient transformer for long sequence time-series forecasting

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.144134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f7516c4-ff09-447a-801e-a19372112b39 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.116497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66db541e-ad46-42a5-8a11-1320bbe56185 · outbound

This paper cites You should return the labels as an np.ndarray of shape (X, ), and for each index, value=1 means the data of the index is abnormal, and value=0 means the data of the index is normal.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models You should return the labels as an np.ndarray of shape (X, ), and for each index, value=1 means the data of the index is abnormal, and value=0 means the data of the index is normal

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.102256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 56397fa5-b4fa-454a-a577-ac61f6de73d4 · outbound

This paper cites Normal Rule 1 \n Normal Rule 2.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Normal Rule 1 \n Normal Rule 2

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.087300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1446baa3-07f3-4b37-8b4b-96f4ee7d8232 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.073184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 153357c3-b774-48bc-bcb7-4c565477ccb1 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.058742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 534327a0-765e-41e1-94b7-d3d5fb6685ab · outbound

This paper cites Figure 12: A prompt template used by the Detection Agent in ARGOS.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Figure 12: A prompt template used by the Detection Agent in ARGOS

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.030923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0ed66fb8-702d-4752-ac1f-f819bd047f02 · outbound

This paper cites The function will take a sample of numpy array with shape (X,2) as input.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models The function will take a sample of numpy array with shape (X,2) as input

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.016040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e1c6f906-7ec8-4226-ae5c-75c9d471d40c · outbound

This paper cites You must not change other logic of the code unrelated to the errors.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models You must not change other logic of the code unrelated to the errors

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:07.986921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 31e1c52b-6b67-4f95-afc1-1f4ab5d9fbde · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.129810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fec078c8-e1eb-4a79-a2b7-e7cc25c17bb2 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:07.973254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f3c8a84f-2e7f-4f25-bc1f-089239882398 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:07.959584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fa6f4f45-34a3-492b-96e8-7a7a7486538a · outbound

This paper cites You will be given the current code for the rules.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models You will be given the current code for the rules

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:07.945293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d749d34f-acec-4a45-8356-f23c8ecab616 · outbound

This paper cites You will be additionally given a code difference comparing the current code with the previous code.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models You will be additionally given a code difference comparing the current code with the previous code

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:07.929956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f57fd706-caee-4e16-841f-439e184007e3 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:07.915591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86acac31-9e26-4bef-9a8f-141cba698682 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 96

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:07.901694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ff4d1e41-106d-429e-8981-f353c7c21806 · outbound

This paper cites Important Notes:.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Important Notes:

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:07.887329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 20c74642-3692-4da8-bb3f-ace6d49b9f07 · outbound

This paper cites You must only use * python begin * and * python end * to wrap your fixed code for only once, don’t use them for any other purpose.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models You must only use *** python begin *** and *** python end *** to wrap your fixed code for only once, don’t use them for any other purpose

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:08.001213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5077148b-74c9-4927-bf61-dc6c9c721417 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 99

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.044870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6fce6fb6-5986-41e2-811f-fc04e05b4f47 · outbound

This paper cites Figure 14: A prompt template used by the Review Agent in ARGOS.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Figure 14: A prompt template used by the Review Agent in ARGOS

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:25:07.872374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9fe2ae94-ea48-4263-b726-04ee3c64d526 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 968

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:25:08.572596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7cfb72f6-8042-4f01-9149-580367c4c460 · outbound

This paper cites an unresolved cited work.

Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models Unresolved cited work

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T15:25:07.376077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5a5a0339-43ec-4c02-852e-797f640d9440 · inbound

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection cites this paper.

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T20:34:14.434210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8da2b79a-a6f5-4044-8e5f-806f40ea7e9c · inbound

From Time Series Analysis to Question Answering: A Survey in the LLM Era cites this paper.

From Time Series Analysis to Question Answering: A Survey in the LLM Era Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:16.008334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bfa8513b-3fc9-4a57-b3ae-09652c931f0c · inbound

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models cites this paper.

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T16:49:28.347649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ba71510-0c13-4f4e-bd25-766172d0725a · inbound

AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning cites this paper.

AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T23:29:46.234809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55d8f00-3159-44d5-bbcf-fa7dc13c7588 · inbound

Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage cites this paper.

Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T01:03:25.224813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2aa6205b-c1c8-4068-8374-866d48c231e6 · inbound

From paper to benchmark: agentic, framework-based reproduction of under-specified methods in machine health intelligence cites this paper.

From paper to benchmark: agentic, framework-based reproduction of under-specified methods in machine health intelligence Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:23:24.658552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b888d6df-5bbd-48ba-81c8-05439bfbadd0 · inbound

Failures Reveal What Metrics Miss: An Evidence-Driven Agent for Recursive Refinement of ECG Classifiers cites this paper.

Failures Reveal What Metrics Miss: An Evidence-Driven Agent for Recursive Refinement of ECG Classifiers Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T15:29:53.923701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models cites this paper.

Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models

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