Paper Citation Record · LEDGER

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector

As of 23 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2501.15053.

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

pith.paper-citation-record.v1
2501.15053 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:44:10.159049Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

30 of 30 outbound references displayed

verified exact3
verified fuzzy24
unresolved3
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f19e8307-35fd-421e-8cf2-af1f91260b25 · outbound

This paper cites Anomaly detection in smart environments: A comprehensive survey,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Anomaly detection in smart environments: A comprehensive survey,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.749836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 705c3272-a53b-4d13-9ac2-42138c29a980 · outbound

This paper cites A systematic literature review of iot time series anomaly detection solutions,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector A systematic literature review of iot time series anomaly detection solutions,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.731178Z

Source-reported events for the cited work

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Observation f7c0510c-6fe1-4b74-b094-feffa0d32924 · outbound

This paper cites Unsupervised anomaly detection in time-series: An exten- sive evaluation and analysis of state-of-the-art methods,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Unsupervised anomaly detection in time-series: An exten- sive evaluation and analysis of state-of-the-art methods,

Reference 3

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Source-reported events for the cited work

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Observation c4e5a699-919e-403b-9fc0-74a42e703936 · outbound

This paper cites Unsuper- vised anomaly detection for iot-based multivariate time series: Existing solutions, performance analysis and future directions,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Unsuper- vised anomaly detection for iot-based multivariate time series: Existing solutions, performance analysis and future directions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.688760Z

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Observation ca68f88a-9218-4608-aa75-8592e5b3bdbc · outbound

This paper cites UoCAD: An unsu- pervised online contextual anomaly detection approach for multivariate time series from smart homes,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector UoCAD: An unsu- pervised online contextual anomaly detection approach for multivariate time series from smart homes,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.671341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 29327b4b-20b6-43ca-9b95-5956611b6f08 · outbound

This paper cites Real-time deep anomaly detection framework for multivariate time-series data in industrial iot,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Real-time deep anomaly detection framework for multivariate time-series data in industrial iot,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.654377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 44119f21-6255-49d0-abf8-98c9507babf7 · outbound

This paper cites Real-time aiot anomaly detection for industrial diesel generator based an efficient deep learning cnn-lstm in industry 4.0,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Real-time aiot anomaly detection for industrial diesel generator based an efficient deep learning cnn-lstm in industry 4.0,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.637196Z

Source-reported events for the cited work

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Observation e7c31575-3684-4f5a-9088-054c6a970021 · outbound

This paper cites Improving performance of log anomaly detection with semantic and time features based on bilstm-attention,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Improving performance of log anomaly detection with semantic and time features based on bilstm-attention,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.616996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e9a2eaa2-9fd2-4da6-a41e-da49223fb238 · outbound

This paper cites Contextual anomaly detection for multivariate time series data,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Contextual anomaly detection for multivariate time series data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.598424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ada3de31-a532-4b6a-8d77-3dbf690eb568 · outbound

This paper cites Time series forecasting and point anomaly detection of sensor signals using lstm neural network architectures,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Time series forecasting and point anomaly detection of sensor signals using lstm neural network architectures,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.582546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7965e897-4c25-458c-be79-7a0b59db9b13 · outbound

This paper cites A hybrid cnn-lstm based approach for anomaly detection systems in sdns,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector A hybrid cnn-lstm based approach for anomaly detection systems in sdns,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.565330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d72fb044-49d9-4a53-a6a9-04407df08952 · outbound

This paper cites Intelligent bilstm-attention-ibpnn method for anomaly detec- tion in financial auditing,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Intelligent bilstm-attention-ibpnn method for anomaly detec- tion in financial auditing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.548443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f6140fa8-aa3d-43e4-b87f-c2ffbcbb010d · outbound

This paper cites Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges,

Reference 13

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Source-reported events for the cited work

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Observation 7d0d1485-276c-44e2-bc5d-98d57b599df5 · outbound

This paper cites Performance anomaly detection in web services: an rnn-based approach using dy- namic quality of service features,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Performance anomaly detection in web services: an rnn-based approach using dy- namic quality of service features,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.523017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f62175ee-cb0a-4d5c-9e2d-ab2a2c59ed4d · outbound

This paper cites Multi-head cnn– rnn for multi-time series anomaly detection: An industrial case study,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Multi-head cnn– rnn for multi-time series anomaly detection: An industrial case study,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.507597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8d727ccc-8644-4e66-91d4-134c3b0854d9 · outbound

This paper cites Contextual anomaly detection on time series: A case study of metro ridership analysis,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Contextual anomaly detection on time series: A case study of metro ridership analysis,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.491290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eb7a0ae8-73bd-4477-b054-0971247a6b73 · outbound

This paper cites Salad: Self-adaptive lightweight anomaly detection for real-time recurrent time series,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Salad: Self-adaptive lightweight anomaly detection for real-time recurrent time series,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.474368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 210d8320-1b01-4f0e-8a35-a4f16c31f551 · outbound

This paper cites RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:44:10.284286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3b673d40-82b4-464e-8018-3e5e1d35c537 · outbound

This paper cites RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:44:10.260249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f4e85f1f-30ca-4491-bf9b-5d1f1d412451 · outbound

This paper cites Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:44:10.228749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 18070c3b-7132-4570-b579-e2dbe1ff3b9a · outbound

This paper cites Contextual anomaly detection framework for big sensor data,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Contextual anomaly detection framework for big sensor data,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.457704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d5063b4f-dc82-47ce-9450-e3dd05147b97 · outbound

This paper cites Time series contextual anomaly detection for detecting market manipulation in stock market,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Time series contextual anomaly detection for detecting market manipulation in stock market,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.442450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 69a4c3b7-1937-4023-b371-a3f92827555f · outbound

This paper cites Contextual anomaly detection for cyber-physical security in smart grids based on an artificial neural network model,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Contextual anomaly detection for cyber-physical security in smart grids based on an artificial neural network model,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.423359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3334d8f0-047a-4082-abd3-efde2c4e103e · outbound

This paper cites Early anomaly detection in smart home: A causal association rule-based approach,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Early anomaly detection in smart home: A causal association rule-based approach,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.400081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2f7b79f0-df19-4dfd-ad6d-61d11525dfac · outbound

This paper cites An adaptive method based on contextual anomaly detection in internet of things through wireless sensor networks,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector An adaptive method based on contextual anomaly detection in internet of things through wireless sensor networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.381646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b1850e20-84a4-456c-9801-f7a88ce0166f · outbound

This paper cites Wisdom of the contexts: active ensemble learning for contextual anomaly detection,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Wisdom of the contexts: active ensemble learning for contextual anomaly detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.364157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 75717b6f-8d6e-46e7-8146-c76095f832ef · outbound

This paper cites View plus - smart indoor air quality monitor,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector View plus - smart indoor air quality monitor,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.344921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b8bd7815-dd00-41e6-a62e-573032924499 · outbound

This paper cites Keras Tuner,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Keras Tuner,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.319176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 83923392-1e61-4470-b3ae-92ff78672018 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T14:44:10.154131Z

Source-reported events for the cited work

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Observation 96cc5e48-1f5c-4f71-b567-40558c288596 · outbound

This paper cites Keras: deep learning library for theano and tensorflow. 2015,.

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector Keras: deep learning library for theano and tensorflow. 2015,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:44:10.301995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.