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Paper Citation Record · LEDGER

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection

As of 8 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2506.02081.

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

pith.paper-citation-record.v1
2506.02081 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:46:58.571644Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

52 of 52 outbound references displayed

  • verified exact0
  • verified fuzzy43
  • unresolved8
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6606a641-2d11-4daf-b7e7-b3aee9853bdf · outbound

This paper cites Springer International Publishing, 2 edn.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Springer International Publishing, 2 edn

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 3075c61c-6325-447c-890d-4c8adbd54aa2 · outbound

This paper cites Transactions on Machine Learning Research (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Transactions on Machine Learning Research (2024)

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e3a8d30f-20b2-488f-bb57-27448470e156 · outbound

This paper cites Language Models are Few-Shot Learners.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Language Models are Few-Shot Learners

Reference 3

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Source-reported events for the cited work

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Observation dab69c37-fdb5-461c-9b6a-36be5860d1c9 · outbound

This paper cites CRC Press, 6th edn.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection CRC Press, 6th edn

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 72edefc6-915e-4aac-9d3a-16f13b2c931f · outbound

This paper cites In: Advances in Neural Information Processing Systems 37 (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Advances in Neural Information Processing Systems 37 (2024)

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 56606399-7f8b-4857-9b07-f6a9963c9b54 · outbound

This paper cites In: Proceedings of the 41st International Conference on Machine Learning (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 41st International Conference on Machine Learning (2024)

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 18e6797f-bcf0-438c-8383-bfcebe14a034 · outbound

This paper cites IFAC Proceedings V olumes46(20), 12–17 (2013).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection IFAC Proceedings V olumes46(20), 12–17 (2013)

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9bb32149-7919-4097-a6ec-758719b18fba · outbound

This paper cites The Annals of Statistics 7, 1–26 (1979).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection The Annals of Statistics 7, 1–26 (1979)

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 624516d5-378f-430c-aa6f-6b52d8537a1b · outbound

This paper cites In: Proceedings of the 40th IEEE International Conference on Data Engineering.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 40th IEEE International Conference on Data Engineering

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5e148ada-7fad-4657-afd2-89c60bd6012c · outbound

This paper cites In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2460dd48-9d23-4d68-ae48-23dc9fdea6fd · outbound

This paper cites In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 9ed46e98-621d-458d-a993-74cae5e0747a · outbound

This paper cites Circulation 101(23), e215–e220 (2000).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Circulation 101(23), e215–e220 (2000)

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9a9b1955-b6dd-46ee-8f7e-1094d145de48 · outbound

This paper cites In: Proceedings of the 41st International Conference on Machine Learning (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 41st International Conference on Machine Learning (2024)

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2a04afca-7123-440c-86c6-dd6e2ed69980 · outbound

This paper cites O’Reilly Media (2019).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection O’Reilly Media (2019)

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 31cb8984-69ee-4185-ba41-ffba8cdfc177 · outbound

This paper cites REALM: Retrieval-Augmented Language Model Pre-Training.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection REALM: Retrieval-Augmented Language Model Pre-Training

Reference 15

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8f1d0dc7-ecb0-4d2e-a4cb-44929ee815b9 · outbound

This paper cites In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3931dbfc-9451-45af-b84d-57fde2083e7c · outbound

This paper cites In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0af68337-7d55-4dc9-ad32-479ac0153544 · outbound

This paper cites In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fe5bfbe8-5a01-4bcd-9073-60b8aa5a1205 · outbound

This paper cites an unresolved cited work.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Unresolved cited work

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 82450d5f-fa11-4180-89fa-75ea74029fe3 · outbound

This paper cites Scientific Data 3(1), 1–9 (2016).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Scientific Data 3(1), 1–9 (2016)

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a9848b53-e402-4233-959e-4e7b82615b95 · outbound

This paper cites In: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (2021).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (2021)

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0c8ef968-3f35-42b4-a093-d495e35a2b64 · outbound

This paper cites In: Proceedings of the 14th International Conference on Machine Learning and Applications.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 14th International Conference on Machine Learning and Applications

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4c5102e5-92bb-4b98-b5f2-69db74ee8d4a · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 58be8fe7-c844-441c-87c3-d897180e9d0d · outbound

This paper cites Proceedings of the VLDB Endowment 17(12), 4229–4232 (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Proceedings of the VLDB Endowment 17(12), 4229–4232 (2024)

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 07afc127-e578-4788-af28-4d9fe15a475e · outbound

This paper cites In: Advances in Neural Information Processing Systems 35 (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Advances in Neural Information Processing Systems 35 (2024)

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 472feb6e-0ee8-4196-9ed1-a4d5e7e05645 · outbound

This paper cites In: Proceedings of the 39th AAAI Conference on Artificial Intelligence.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 39th AAAI Conference on Artificial Intelligence

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ccefff29-36b4-4517-bcc1-007a23d85f8f · outbound

This paper cites IEEE Transactions on Fuzzy Systems 23(3), 688– 700 (2014).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection IEEE Transactions on Fuzzy Systems 23(3), 688– 700 (2014)

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f8b444b0-0a75-4d29-8503-5aaa2ba51192 · outbound

This paper cites GPT-4 Technical Report.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection GPT-4 Technical Report

Reference 28

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:46:58.317184Z digest=sha256:5259d18a837dcf1dab8900fbc62f23e15a85011bc66a24db66b1b354c55fc894

Observation 790831b0-4a57-4c7c-9fa2-98e075fb5b83 · outbound

This paper cites Proceedings of the VLDB Endowment 15(11), 2774–2787 (2022).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Proceedings of the VLDB Endowment 15(11), 2774–2787 (2022)

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:00.340512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 59505b2e-df9a-4a22-be9a-88b46b987c6a · outbound

This paper cites In: Proceedings of the ACM SIGMOD International Conference on Management of Data.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the ACM SIGMOD International Conference on Management of Data

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:00.263152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a7794131-7b3f-4000-a40c-d9fe5fffc1b6 · outbound

This paper cites Proceedings of the VLDB Endowment 15(8), 1697–1711 (2022).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Proceedings of the VLDB Endowment 15(8), 1697–1711 (2022)

Reference 31

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 32bdab39-a5c8-48d4-82db-b12f88cc47dc · outbound

This paper cites In: Proceedings of the ACM SIGMOD International Conference on Management of Data (2020).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the ACM SIGMOD International Conference on Management of Data (2020)

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:00.109465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.352985Z digest=sha256:9836d11eb984d9885379393c50aa938f416b5a30d6ff38b2589db9f1f3aff195

Observation d6752a4d-e4df-4a30-bce2-7400fc2053a0 · outbound

This paper cites Proceedings of the VLDB Endowment 15(9), 1779–1797 (2022).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Proceedings of the VLDB Endowment 15(9), 1779–1797 (2022)

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:00.031119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2639a129-b5eb-40d0-8c75-024f997031fb · outbound

This paper cites In: Pro- ceedings of the 13th International Conference on Learning Representations (2025).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Pro- ceedings of the 13th International Conference on Learning Representations (2025)

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.961847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.371601Z digest=sha256:40d84eb848429fef164cede8ffa2db3056128823dbd010eff7da6ebf5a308db9

Observation 7c2494f4-ce0c-4637-8224-456ad89b502b · outbound

This paper cites In: Proceedings of the 13th International Conference on Learning Representations (2025).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 13th International Conference on Learning Representations (2025)

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.879909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.378709Z digest=sha256:aee61f1b1db6647f53342a63243998b7d68f0e9a0edfe1bb33de130242f45d64

Observation b892a94a-83b9-47a4-97e7-937111625f8c · outbound

This paper cites In: Proceedings of the 12th International Conference on Learning Representations (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 12th International Conference on Learning Representations (2024)

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.789557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.389729Z digest=sha256:918088da85a47ae700e1b8ea0e4f2465ba5674bc98f3399d8e45509ff5292326

Observation 54d70487-b607-4da4-824c-e99afa2b8705 · outbound

This paper cites In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.700437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.397302Z digest=sha256:4331d4e243740c26d7845c5a5342264789506291a46b10088d926872bd5f5b6d

Observation 925628b4-9c9d-44e8-9ae0-88d35584649a · outbound

This paper cites In: Proceedings of the 40th IEEE International Conference on Data Engineering.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 40th IEEE International Conference on Data Engineering

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.619655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.407999Z digest=sha256:59ae45e6f705d4b81738b95dd11a330a1e71e97b4f59fb4183238cc7ab13dc22

Observation e35777b3-8843-450d-bb9e-2927a79ca665 · outbound

This paper cites In: Advances in Neural Information Processing Systems 31 (2018).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Advances in Neural Information Processing Systems 31 (2018)

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.451476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.420560Z digest=sha256:8ff8bf752ab708af1ad17ab195b90f750976e8c929aa70dc7a2d368c3e84b2a1

Observation 18f67957-b82c-4408-84e9-ab756433a60e · outbound

This paper cites In: Advances in Neural Information Processing Systems 30 (2017).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Advances in Neural Information Processing Systems 30 (2017)

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.380413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.431283Z digest=sha256:d3e33aff08e436a2a9de6c1432253187488389c42150994687e6c5e7ddad02aa

Observation 93476f9b-c083-45d1-9f6d-dd7c4d94caa0 · outbound

This paper cites In: Proceedings of the 41st International Conference on Machine Learning (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 41st International Conference on Machine Learning (2024)

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.294135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.440694Z digest=sha256:264823dcc23dbfd55162cf603162671b366059f3b9edc74f465d9191f9b231c1

Observation d86d4073-4a46-4581-9296-452d12f2a0a7 · outbound

This paper cites IEEE Transactions on Knowledge and Data Engineering 35(3), 2421–2429 (2021).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection IEEE Transactions on Knowledge and Data Engineering 35(3), 2421–2429 (2021)

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.222264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.449093Z digest=sha256:94d5195703de6b40751cb9c7fad8f0d5b319da0158d75c3fa1ed94482afa1484

Observation e2a9e4d3-cf98-4425-a482-81de4a37f98c · outbound

This paper cites In: Proceedings of the 13th International Conference on Learning Representations (2025).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 13th International Conference on Learning Representations (2025)

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.144864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.459036Z digest=sha256:e8cf65629bd03e28f52db3a774dfd6e712b666f3f12383d57dbc641f381353b2

Observation 0de374df-944c-4599-b982-cb4fdaf0f899 · outbound

This paper cites In: Proceedings of the ACM on Web Conference.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the ACM on Web Conference

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.067858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.467326Z digest=sha256:72acc79c31b4e9c625a8741685e050617e4353d81b103c0f543100545f00ad5a

Observation 01e8fd74-3e40-428f-a891-3437f19291e4 · outbound

This paper cites In: Proceedings of the 10th International Conference on Learning Representations (2022).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 10th International Conference on Learning Representations (2022)

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:59.018524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.474340Z digest=sha256:7d9ac5db374f9baa6f51713e0e153e32f2a9d008c29bc5016404ed7e897b5ed0

Observation b8e1567d-fe6e-4752-b5ce-00234d861f78 · outbound

This paper cites In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:58.951458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.480901Z digest=sha256:066048ca62a67d571a4a170e844cacc6011f1de15f3fdaf31bbcf7e10bd083ca

Observation c1a146d8-eba5-4343-8ee3-83e108f45b56 · outbound

This paper cites In: Proceedings of the 16th IEEE International Conference on Data Mining.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 16th IEEE International Conference on Data Mining

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:58.872152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.503487Z digest=sha256:de1a0b899f4e8ca213409fb66d084f2f1fc27a9031368a8e8fdfe2aca4a9e6d0

Observation 45a4a301-31ba-4ec3-acb6-7a0f364a80e9 · outbound

This paper cites ACM Computing Surveys 57(1), 1–42 (2024).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection ACM Computing Surveys 57(1), 1–42 (2024)

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T11:46:58.519458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:46:58.519458Z digest=sha256:3c6d20c1bc894f2dcf248ca04f76a4a0bcdce55fd1c9871c306b6c3a2e79910b

Observation efccf8a8-8624-4f22-9cf6-d357e8a906d5 · outbound

This paper cites In: Advances in Neural Information Processing Systems 35 (2022).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Advances in Neural Information Processing Systems 35 (2022)

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:58.767369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.530218Z digest=sha256:0403d91895a57216f56702cb30ea5757dc3d7eaeadb31e8caebd342982baa7e2

Observation bef4f701-eef2-4670-9ae9-5384e3e0be79 · outbound

This paper cites In: Proceedings of the 13th International Conference on Learning Representations (2025).

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection In: Proceedings of the 13th International Conference on Learning Representations (2025)

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:46:58.686994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.539200Z digest=sha256:5b3e08a78a70c0678069e752aef26e42b41818da5c70b30ff1fcaf3246297903

Observation 82946ff3-95ca-4f11-9fa7-9287a5a04eea · outbound

This paper cites an unresolved cited work.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:46:58.652732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:46:58.559049Z digest=sha256:ee1ef47254ccf706da29b6ecd479e429df0a695b3f4313368d71bbd54945cfaa

Observation 1ed83cda-cb34-48ff-a725-afb3f2fcda15 · outbound

This paper cites See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers.

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers

Reference 52

Resolution
malformed identifier
no resolver link, observed 2026-08-07T11:46:58.571644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:46:58.571644Z digest=sha256:9a35d6feef0ddfa92b06bff773204e0be3abb8a1104d1be460d04a05a47ed847

Pith citing papers

No inbound Pith citation observations are available.