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Paper Citation Record · LEDGER

LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:1607.00148.

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

pith.paper-citation-record.v1
1607.00148 v2

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:49:28.612642Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T08:19:44.931566Z

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Outbound references

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Pith citing papers

Observation 368439f8-44a1-4aa3-9ddc-38970ada428a · inbound

An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series cites this paper.

An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 11

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local_arxiv, observed 2026-05-24T20:04:52.827576Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 91932bf9-66e3-412b-aa90-14d00f1cb909 · inbound

An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing cites this paper.

An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 15

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local_arxiv, observed 2026-05-24T15:36:14.483019Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-24T15:35:21.560626Z digest=sha256:b3598d895030b9d6ac52cb597308a0bcf7f0195d8e9eee9c826ec01a26421f6f

Observation e85c7907-a193-4d59-b299-658f42faac17 · inbound

Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality cites this paper.

Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 23

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no resolver link, observed 2026-08-14T15:26:55.183808Z

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source=pdf_text observed=2026-08-14T15:26:55.183808Z digest=sha256:9af95ba205728ad9fad3d91841e88f3d0fed3d738fc8b8d9dd96ebfb98c4d33a

Observation 97661ee7-0543-4ce6-a858-f0ebf9bcc95d · inbound

Finding One's Bearings in the Hyperparameter Landscape of a Wide-Kernel Convolutional Fault Detector cites this paper.

Finding One's Bearings in the Hyperparameter Landscape of a Wide-Kernel Convolutional Fault Detector LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 25

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no resolver link, observed 2026-08-12T17:40:57.812342Z

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source=pdf_text observed=2026-08-12T17:40:57.812342Z digest=sha256:6545f5f6f2b6f89eda371baf17afedd5d78ff832cf1bd3ddc324a750afad39a8

Observation f3308a57-2618-4d34-8b3e-e30126c5013c · inbound

A Machine Learning-based Anomaly Detection Framework in Life Insurance Contracts cites this paper.

A Machine Learning-based Anomaly Detection Framework in Life Insurance Contracts LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 24

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source=arxiv_source observed=2026-08-12T12:10:47.711759Z digest=sha256:b0a441c81fb7a00888b9e2789521f984d0ff4d30e13241aa2119614476b02aa3

Observation fa85c7a8-6f2a-483a-972b-2cbf555b38e4 · inbound

Leveraging A New GAN-based Transformer with ECDH Crypto-system for Enhancing Energy Theft Detection in Smart Grid cites this paper.

Leveraging A New GAN-based Transformer with ECDH Crypto-system for Enhancing Energy Theft Detection in Smart Grid LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 25

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source=pdf_text observed=2026-08-12T11:41:50.260510Z digest=sha256:e6e7468841c1111e34adf063a50535bb0f347de1a6e045d4abadd49042b82900

Observation b0004f6e-120d-4f22-bdb6-a9dd2bd86a65 · inbound

F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain Information cites this paper.

F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain Information LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 31

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source=pdf_text observed=2026-08-11T23:29:57.873088Z digest=sha256:a474def56bdf6a49414b950fdffc41ed24eaff48d655f8219f64770e9d368f20

Observation 04afc880-b1f0-4055-b7a9-d37fa6ee696e · inbound

A Bidirectional Long Short Term Memory Approach for Infrastructure Health Monitoring Using On-board Vibration Response cites this paper.

A Bidirectional Long Short Term Memory Approach for Infrastructure Health Monitoring Using On-board Vibration Response LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 39

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source=pdf_text observed=2026-08-11T23:17:28.736886Z digest=sha256:987bdc7c3704d8d324aadd0a3aa2ca832fafc659a29b5c78e516ab9de66149ab

Observation 265ec6d4-3ba5-438f-a9cc-bf4a86be16bd · inbound

CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection cites this paper.

CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 53

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source=pdf_text observed=2026-08-11T04:30:42.829108Z digest=sha256:87f9d2eac0d9f63e21710d261ac1739e5b57b15d6d3f5fb866afcf3e419e7f94

Observation 096123d0-4988-4100-bc69-0e3bf9a566ae · inbound

Dive into Time-Series Anomaly Detection: A Decade Review cites this paper.

Dive into Time-Series Anomaly Detection: A Decade Review LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 152

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source=pdf_text observed=2026-08-10T23:22:31.428460Z digest=sha256:e87f7fa7edad56b9be8840696743d5566795c14c1687738aec5fe667a6b4ca27

Observation 9d633d68-f587-4778-92fb-c311555f83b0 · inbound

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework cites this paper.

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 49

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source=pdf_text observed=2026-08-10T23:04:09.375767Z digest=sha256:58e8cfdeb9080b31004659b787423a94d328afebaedd9d8571fa70929911671d

Observation 7468214f-e313-4b21-863c-d6457cac38b8 · inbound

STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via cites this paper.

STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 34

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source=pdf_text observed=2026-08-10T20:38:48.366168Z digest=sha256:a9ad19fee6233859f53e45022892057a85f60bab2f666f638531b598d55a7e76

Observation c807ee32-fee1-4d33-acc0-07def5cf3740 · inbound

CICADA: Cross-Domain Interpretable Coding for Anomaly Detection and Adaptation in Multivariate Time Series cites this paper.

CICADA: Cross-Domain Interpretable Coding for Anomaly Detection and Adaptation in Multivariate Time Series LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 27

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source=pdf_text observed=2026-08-16T04:49:28.612642Z digest=sha256:4e52d7b3d79ed36b7ea8489ee9a380f855c64fed118233f219697687960f42ff

Observation 8514ee5d-b7fd-41f5-8cd9-f1d5b22fd36e · inbound

An Explainable Anomaly Detection Framework for Monitoring Depression and Anxiety Using Consumer Wearable Devices cites this paper.

An Explainable Anomaly Detection Framework for Monitoring Depression and Anxiety Using Consumer Wearable Devices LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 62

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source=pdf_text observed=2026-08-16T00:06:50.666995Z digest=sha256:12f51bfc6db8b85809271d2debf1193bc22de40e92193140c55011cde3082984

Observation e561264c-fd61-4ec8-8df0-f85cde62f5d1 · inbound

Anomaly Detection for Non-stationary Time Series using Recurrent Wavelet Probabilistic Neural Network cites this paper.

Anomaly Detection for Non-stationary Time Series using Recurrent Wavelet Probabilistic Neural Network LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 14

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no resolver link, observed 2026-08-15T21:00:39.123999Z

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source=pdf_text observed=2026-08-15T21:00:39.123999Z digest=sha256:e869555c97745999e651f7fc48fd57cc647ef10431970bef2cd0e1e93e2bec98

Observation ba0c8233-9c2f-44b0-8657-c5a0b952f13e · inbound

Robust and Explainable Detector of Time Series Anomaly via Augmenting Multiclass Pseudo-Anomalies cites this paper.

Robust and Explainable Detector of Time Series Anomaly via Augmenting Multiclass Pseudo-Anomalies LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 27

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no resolver link, observed 2026-08-07T13:52:28.965089Z

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source=pdf_text observed=2026-08-07T13:52:28.965089Z digest=sha256:8374d8e56e0d73c681907f33230ae8507be4a195883c369aad1031e654fb92b3

Observation 9ea2eba0-69dd-4801-af8a-8a8de36955a1 · inbound

A Survey of Deep Learning Video Super-Resolution cites this paper.

A Survey of Deep Learning Video Super-Resolution LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 87

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source=pdf_text observed=2026-08-07T11:25:15.642266Z digest=sha256:8405c487db396e72e9fd6a93eb4cff168f84b8de69a35e7c3e4064118a212430

Observation f1ba4e36-f2d3-467e-9237-4a7b1cea5f2f · inbound

Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles cites this paper.

Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 14

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source=pdf_text observed=2026-08-07T00:42:04.536756Z digest=sha256:a9b9ea640275187e4e5bb874d6e60e4d033b179e93a5743d8cbc522fe868cb1e

Observation 42d66948-30c6-4b26-beac-2212c249472e · inbound

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments cites this paper.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 1

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source=pdf_text observed=2026-08-04T23:42:39.070545Z digest=sha256:f59def4da4f0444b97f2ecebcff8b96fe1caf8730ecff8fabb7b78b014800a89

Observation 3a570572-7ca1-489e-8281-f16ba8fef621 · inbound

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN cites this paper.

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 20

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verified exact
local_arxiv, observed 2026-05-18T11:56:19.817541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T11:54:34.243253Z digest=sha256:6e00c20f03c5b4fb5bcd7ca3f84085ec4222d6749fc784072340a6744120c3c8

Observation 91bf2be1-9016-489f-ace6-3ca0fa153e70 · inbound

Causally-Constrained Probabilistic Forecasting for Time-Series Anomaly Detection cites this paper.

Causally-Constrained Probabilistic Forecasting for Time-Series Anomaly Detection LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 12

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arxiv_id, observed 2026-05-10T10:14:10.447904Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T05:03:21.126660Z digest=sha256:f88c5c9c2b2e5dc611462b6bd7579403cb17d307c74896f0733c07a72998de90

Observation 0797b6d8-c234-45ef-b702-181b2a5a6309 · inbound

PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs cites this paper.

PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 5

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arxiv_id, observed 2026-05-11T14:56:05.560894Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-09T20:52:49.813619Z digest=sha256:9c196e0ef5f80b5fa3f12ec03b03a8e2010ea287e0af816fdab6055a8c60e7e8

Observation e360a7b9-d3fc-403c-b30f-0d23108eda69 · inbound

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

Detecting Time Series Anomalies Like an Expert: A Multi-Agent LLM Framework with Specialized Analyzers LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 21

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arxiv_id, observed 2026-05-11T19:31:09.993080Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T11:43:28.398396Z digest=sha256:01dd4c02e9614f887cf2ad0f0724b15f374d0d6219043f11ee2967366cd927fc

Observation 057a6e8b-0934-489d-92a0-a3d0d9fa1254 · inbound

E4GEN: Event-level Explainable Extreme-Enhanced Time-series Generation cites this paper.

E4GEN: Event-level Explainable Extreme-Enhanced Time-series Generation LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 42

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local_arxiv, observed 2026-07-01T22:06:16.958537Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T15:42:04.524729Z digest=sha256:f038be2937fc74c06c655897a82aafc39cc3a34603523b3a3cb09ddcb805ed0d

Observation 92f3dd2a-749e-44d5-a3b4-f25c69a455a5 · inbound

Learning a Normal World Model for Few-Shot Boundary-Calibrated Abnormality Detection cites this paper.

Learning a Normal World Model for Few-Shot Boundary-Calibrated Abnormality Detection LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 32

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local_arxiv, observed 2026-07-04T08:19:44.932709Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-26T11:45:42.571013Z digest=sha256:ea1faaf584d075fe1f799ebb740536fe71c9f1a48fb539f768fbeaa5e7f4c7bc

Observation 27abacbe-6e60-4de4-a505-f2588b8e76e1 · inbound

Federated Low-Rank Koopman Learning for Multivariate Time-Series Anomaly Detection in IoT Systems cites this paper.

Federated Low-Rank Koopman Learning for Multivariate Time-Series Anomaly Detection in IoT Systems LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 6

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source=pdf_text observed=2026-07-13T01:18:00.991134Z digest=sha256:c08efa2fc50df6bf0fa2cb02339295e4f78f762ef96d310cc134b4128a8ba607

Observation e0d3b2c4-ebde-49c0-acca-5b6931f0e2e6 · inbound

Label-free Industrial Fault Detection via Adversarial Inverse Reinforcement Learning: A System for Run-to-Failure Prognostics cites this paper.

Label-free Industrial Fault Detection via Adversarial Inverse Reinforcement Learning: A System for Run-to-Failure Prognostics LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 19

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