Paper Citation Record · LEDGER

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection

As of 19 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2603.12916.

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

pith.paper-citation-record.v1
2603.12916 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T22:02:51.907844Z

measured 37 of 37 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 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

37 of 37 outbound references displayed

verified exact4
verified fuzzy0
unresolved27
parse uncertain0
malformed identifier5
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a607b5f8-655a-47e2-8f26-3dc7d4b79347 · outbound

This paper cites Competition and Attraction Improve Model Fusion.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Competition and Attraction Improve Model Fusion

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-07-14T22:10:48.767648Z

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.

Observation 952fbc39-8d54-452a-8d14-aa50090e047a · outbound

This paper cites Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

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Observation 709dd53c-d8cf-44d4-8c8f-c131340985d2 · outbound

This paper cites In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Min- ing.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Min- ing

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 4dadb95c-87fb-4a20-bdf8-163e6db885ea · outbound

This paper cites Layer Normalization.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Layer Normalization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ebeb192-db3c-49bd-846f-a4b90e9dd3d3 · outbound

This paper cites LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation f59afab7-fc05-4128-9a6a-9e6721900dc3 · outbound

This paper cites an unresolved cited work.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Unresolved cited work

Reference 6

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Observation 9cc42358-ed35-43e5-b676-11f44fe35bcf · outbound

This paper cites https://doi.org/10.1145/335191.335388, https://dl.acm.org/doi/10.1145/335191.335388 Predictable Query Dynamics for Time Series Anomaly Detection 15.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection https://doi.org/10.1145/335191.335388, https://dl.acm.org/doi/10.1145/335191.335388 Predictable Query Dynamics for Time Series Anomaly Detection 15

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 1e0bbb61-0e63-4e52-8f14-4b2395476b6c · outbound

This paper cites an unresolved cited work.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

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Observation 45103419-ce49-4bc5-8993-39e9c03ee447 · outbound

This paper cites In: 2018 IEEE/CVF Conference on Com- puter Vision and Pattern Recognition.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: 2018 IEEE/CVF Conference on Com- puter Vision and Pattern Recognition

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 859eb009-ec42-4a16-8687-e8b19131f169 · outbound

This paper cites In: Proceedings of the 15th International Joint Conference on Computational Intelligence.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: Proceedings of the 15th International Joint Conference on Computational Intelligence

Reference 10

Resolution: verified exact; doi, observed 2026-07-14T22:10:48.856952Z

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.

Observation d824f529-5e42-4b7a-a832-fc87c0099742 · outbound

This paper cites IEEE Transactions on Information Theory13(1), 21–27 (January 1967).https://doi.org/10.1109/TIT.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection IEEE Transactions on Information Theory13(1), 21–27 (January 1967).https://doi.org/10.1109/TIT

Reference 11

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Observation acdc9c14-1724-482a-b508-735722db79df · outbound

This paper cites Graph Neural Network-Based Anomaly Detection in Multivariate Time Series.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Graph Neural Network-Based Anomaly Detection in Multivariate Time Series

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 9f3bb5a4-fbc0-4db8-81cd-5c7815cf604a · outbound

This paper cites an unresolved cited work.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Unresolved cited work

Reference 13

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Observation 60da1ac1-6a2b-4c98-905a-3e9857fa91ab · outbound

This paper cites Bootstrap your own latent: A new approach to self-supervised Learning.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Bootstrap your own latent: A new approach to self-supervised Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation d453435b-0a12-4346-a946-3b5e33702cd6 · outbound

This paper cites IEEE Trans- actions on Knowledge and Data Engineering33(4), 1479–1489 (Apr 2021).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection IEEE Trans- actions on Knowledge and Data Engineering33(4), 1479–1489 (Apr 2021)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation d4ba8270-1dfd-4173-af69-aa27332faff5 · outbound

This paper cites Pat- tern Recognition Letters24(9), 1641–1650 (2003).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Pat- tern Recognition Letters24(9), 1641–1650 (2003)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation abe04b24-9eac-4f3d-af7f-66613d3f0634 · outbound

This paper cites Temporal Convolutional Networks for Action Segmentation and Detection.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Temporal Convolutional Networks for Action Segmentation and Detection

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 1986b4d2-9d8e-43bf-8a62-7fcd3f802342 · outbound

This paper cites IEEE Trans- actions on Neural Networks and Learning Systems32(3), 1177–1191 (Mar 2021).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection IEEE Trans- actions on Neural Networks and Learning Systems32(3), 1177–1191 (Mar 2021)

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-14T22:10:48.819761Z

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.

Observation 15be2462-4916-40b6-8080-0fe2230e80d1 · outbound

This paper cites COPOD: Copula-Based Outlier Detection.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection COPOD: Copula-Based Outlier Detection

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Unavailable: canonical work link unavailable.

Observation 4cac205b-8534-453b-9fe9-dfb1caff3fa3 · outbound

This paper cites International Jour- nal of Forecasting37(4), 1748–1764 (Oct 2021).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection International Jour- nal of Forecasting37(4), 1748–1764 (Oct 2021)

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b6873cd-f683-4f35-8fac-2e325352283b · outbound

This paper cites In: 2008 Eighth IEEE In- ternational Conference on Data Mining.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: 2008 Eighth IEEE In- ternational Conference on Data Mining

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 47f8d9b5-2301-41f4-85f9-c3019d354d82 · outbound

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

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: Advances in Neural Information Processing Systems 37

Reference 22

Resolution: malformed identifier; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

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Observation 97ccf8fc-53c0-47d6-aafe-b89fcdb3ccde · outbound

This paper cites Decoupled Weight Decay Regularization.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Decoupled Weight Decay Regularization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 2ee40161-4ba3-4849-be06-666a7500bacc · outbound

This paper cites an unresolved cited work.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16c52192-6062-4383-81e2-746344a3d5b3 · outbound

This paper cites Proceedings of the VLDB Endowment15(11), 2774–2787 (Jul 2022).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Proceedings of the VLDB Endowment15(11), 2774–2787 (Jul 2022)

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eee52783-db6b-4536-9e6e-539491647744 · outbound

This paper cites In: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)

Reference 26

Resolution: malformed identifier; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

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Observation 25b7bb29-1b66-437f-b135-66696cd4837d · outbound

This paper cites International Journal of Data Mining and Bioinfor- matics22(4), 389 (2019).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection International Journal of Data Mining and Bioinfor- matics22(4), 389 (2019)

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-14T22:10:48.774545Z

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.

Observation 6219fd12-b117-4d54-8e0b-4a2f0d975d0e · outbound

This paper cites In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a33af0a5-2626-4274-ae47-09b2ce2e68c0 · outbound

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

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation e9a46cb9-40d5-432e-bfa7-a0d614f58040 · outbound

This paper cites In: Proceedings of the 31st International Conference on Neural Information Processing Systems.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection In: Proceedings of the 31st International Conference on Neural Information Processing Systems

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26d15d44-9c65-492c-9f2f-bba390112024 · outbound

This paper cites Engineering Applications of Artificial Intelligence 104, 104354 (Sep 2021).

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Engineering Applications of Artificial Intelligence 104, 104354 (Sep 2021)

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-14T22:10:48.812826Z

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.

Observation 3aa00573-c4c3-4ef4-a4d9-3d378662e0a2 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

Source-reported events for the cited work

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Observation 26b6681b-433b-442f-b13f-528bfba11c5c · outbound

This paper cites Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation ccda3df8-24fd-4622-81a6-87410f7c52d7 · outbound

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

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

Reference 34

Resolution: malformed identifier; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 3843aa8d-458a-4719-884d-030ee267132d · outbound

This paper cites FITS: Modeling Time Series with $10k$ Parameters.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection FITS: Modeling Time Series with $10k$ Parameters

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Observation 0e070967-4ef9-427b-8652-bf73b0df8a2c · outbound

This paper cites an unresolved cited work.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection Unresolved cited work

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Unavailable: canonical work link unavailable.

Observation 9e79aa33-cf4f-4e7a-b2f5-b34c9013e5ff · outbound

This paper cites One Fits All:Power General Time Series Analysis by Pretrained LM.

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-14T22:02:51.907844Z

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Pith citing papers

No inbound Pith citation observations are available.