Paper Citation Record · LEDGER

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model

As of 18 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2507.14668.

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

pith.paper-citation-record.v1
2507.14668 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

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measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:48:02.551884Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:48:02.654308Z

Reference resolution

50 of 50 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 62d0d5d0-3501-4972-bb84-76530247b264 · outbound

This paper cites Dual-hybrid intrusion detection system to detect false data injection in smart grids,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Dual-hybrid intrusion detection system to detect false data injection in smart grids,

Reference 1

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Observation 22132384-9183-49e0-a32e-83010e766380 · outbound

This paper cites False data injection attack detection for virtual coupling systems of heavy-haul trains: A deep learning approach,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model False data injection attack detection for virtual coupling systems of heavy-haul trains: A deep learning approach,

Reference 2

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6e7dbe1d-93a5-424f-86e3-674cf4bd5d87 · outbound

This paper cites Graph neural network-based approach for detecting false data injection attacks on voltage stability,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Graph neural network-based approach for detecting false data injection attacks on voltage stability,

Reference 3

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Observation c491069f-85ab-4217-ac1b-01839b89dba7 · outbound

This paper cites An advanced defense mechanism for detecting false data injection attacks in cyber-physical systems through feature selection based-machine learning algorithms,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model An advanced defense mechanism for detecting false data injection attacks in cyber-physical systems through feature selection based-machine learning algorithms,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ca41e25c-5288-49e9-a067-bc8f6a39ba36 · outbound

This paper cites A new false data injection detection protocol based machine learning for p2p energy transaction between cevs,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model A new false data injection detection protocol based machine learning for p2p energy transaction between cevs,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.464844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b77baf78-618e-403a-9946-19c9dc45cc6b · outbound

This paper cites Automated deep cnn-lstm architecture design for solar irradiance forecasting,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Automated deep cnn-lstm architecture design for solar irradiance forecasting,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.421596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d9075a4-e125-461a-abaa-72b0acbbde57 · outbound

This paper cites A photovoltaic power forecasting model based on dendritic neuron networks with the aid of wavelet transform,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model A photovoltaic power forecasting model based on dendritic neuron networks with the aid of wavelet transform,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 77d18a3d-a75a-48f2-89ab-5be9281ac0c1 · outbound

This paper cites A comparative study on short-term pv power forecasting using decomposition based optimized extreme learning machine algorithm,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model A comparative study on short-term pv power forecasting using decomposition based optimized extreme learning machine algorithm,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.374282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1c0868f0-cc3e-4cd6-a6c2-ea71140e93fd · outbound

This paper cites Short-term photovoltaic power generation forecasting based on random forest feature selection and ceemd: A case study,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Short-term photovoltaic power generation forecasting based on random forest feature selection and ceemd: A case study,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7640cfae-2341-49e9-a196-856462ca94b9 · outbound

This paper cites an unresolved cited work.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Unresolved cited work

Reference 10

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Observation 300d449d-2e6c-4e9a-b111-9d5100fb4c32 · outbound

This paper cites Mixed-Precision Embedding Using a Cache.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Mixed-Precision Embedding Using a Cache

Reference 11

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Observation 69643b6d-f5ad-4259-9e19-51a10661ef06 · outbound

This paper cites Learnable embedding sizes for recommender systems,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Learnable embedding sizes for recommender systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.330866Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 96f0d20c-619d-4534-833c-fbcdbd87947a · outbound

This paper cites an unresolved cited work.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Unresolved cited work

Reference 13

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Source-reported events for the cited work

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Observation 4534c0d4-0ef8-493d-b844-d07cd93dcae2 · outbound

This paper cites A novel group recommendation model with two-stage deep learning,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model A novel group recommendation model with two-stage deep learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.302250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4e9894d4-94bf-4f48-9502-5e098eff348f · outbound

This paper cites Deep residual networks for image recognition,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Deep residual networks for image recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.287220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68ae334d-0b4f-4771-a9cb-1b899c83d7f0 · outbound

This paper cites Attention is all you need,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Attention is all you need,

Reference 16

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Source-reported events for the cited work

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Observation 7d59cb4d-9f1b-4a8b-9aea-1f80c1ee0308 · outbound

This paper cites Understanding capacity-driven scale-out neural recommendation infer- ence,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Understanding capacity-driven scale-out neural recommendation infer- ence,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.262830Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 505eeb6d-68c0-4750-ad39-65cf15095340 · outbound

This paper cites Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems

Reference 18

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28a060fa-4072-463f-b4b7-6782130a071b · outbound

This paper cites Software-hardware co-design for fast and scalable training of deep learning recommendation models,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Software-hardware co-design for fast and scalable training of deep learning recommendation models,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cc598e7d-3ee9-41a6-bc3c-e0d85cc6dc51 · outbound

This paper cites Nvidia A100 GPU: Performance & innovation for gpu computing,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Nvidia A100 GPU: Performance & innovation for gpu computing,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.248813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 41f26f0a-a7ad-49f3-bdfb-f2887340d48e · outbound

This paper cites Nvidia merlin hugectr,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Nvidia merlin hugectr,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.234600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 40d4c43a-4966-42f5-935b-3f087421ffd0 · outbound

This paper cites Post-Training 4-bit Quantization on Embedding Tables.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Post-Training 4-bit Quantization on Embedding Tables

Reference 22

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Source-reported events for the cited work

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Observation 629cf0f5-7f2e-40cb-b6e4-7314ca2f69fd · outbound

This paper cites TT-Rec: Tensor train compres- sion for deep learning recommendation models,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model TT-Rec: Tensor train compres- sion for deep learning recommendation models,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.220829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 84f0e31b-1536-419e-b1bb-5f5be24b6304 · outbound

This paper cites Deep Learning Recommendation Model for Personalization and Recommendation Systems.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Deep Learning Recommendation Model for Personalization and Recommendation Systems

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T16:00:15.285530Z

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Observation 9b52dd65-f9fc-40b5-93f1-f5c2860863d1 · outbound

This paper cites Accelerating recommendation system training by leveraging popular choices,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Accelerating recommendation system training by leveraging popular choices,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.207149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fd2cee22-1090-46f7-80e9-bc608607d360 · outbound

This paper cites Parallax: Sparsity-aware data parallel training of deep neural networks,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Parallax: Sparsity-aware data parallel training of deep neural networks,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T16:00:15.294172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f04060ed-c7ae-43f0-a8fa-a013b4a1dadb · outbound

This paper cites Scaling distributed machine learning with the parameter server,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Scaling distributed machine learning with the parameter server,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.193497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 967b0071-8a0e-45c0-ae3e-226f19613aea · outbound

This paper cites Scalefreectr: Mixcache-based distributed training system for ctr models with huge embedding table,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Scalefreectr: Mixcache-based distributed training system for ctr models with huge embedding table,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T16:00:15.303091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa95342a-3d75-46d1-90bb-1e3d6d7e4b63 · outbound

This paper cites Centaur: a chiplet-based, hybrid sparse-dense accelerator for personalized recommendations,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Centaur: a chiplet-based, hybrid sparse-dense accelerator for personalized recommendations,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T16:00:15.307164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 119d7d2d-2dce-4e6c-a08f-09a3452ebcd9 · outbound

This paper cites Aibox: Ctr prediction model training on a single node,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Aibox: Ctr prediction model training on a single node,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T16:00:15.311324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9966067-2ce6-45b1-8cd1-b39278cea918 · outbound

This paper cites Unisolar: An open dataset of photovoltaic solar energy generation in a large multi-campus university setting,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Unisolar: An open dataset of photovoltaic solar energy generation in a large multi-campus university setting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.178714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c9527721-97b9-4313-a1ea-07f38cfa6156 · outbound

This paper cites Compressing recurrent neural network with tensor train,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Compressing recurrent neural network with tensor train,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.164528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ba90c0db-7b9b-45c9-8977-53fec5c2b9fb · outbound

This paper cites Hardware-enabled efficient data processing with tensor- train decomposition,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Hardware-enabled efficient data processing with tensor- train decomposition,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.147960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4fe3985a-bbde-4e16-8c88-17e7167d67b1 · outbound

This paper cites Tensor-train decomposition,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Tensor-train decomposition,

Reference 34

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Source-reported events for the cited work

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Observation 8cd27196-a62a-47a2-98a6-23eb1adac22a · outbound

This paper cites Adtt: a highly efficient distributed tensor-train decomposition method for iiot big data,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Adtt: a highly efficient distributed tensor-train decomposition method for iiot big data,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.133563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3c11e341-82b5-401a-b5a4-8f6e925374f7 · outbound

This paper cites Tensor train decomposition on tensorflow (t3f),.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Tensor train decomposition on tensorflow (t3f),

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.118575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a6a44fad-5e78-4d6c-bf4f-1b5efcf6dbcc · outbound

This paper cites Tensorized embedding layers,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Tensorized embedding layers,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.104333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 439f708b-eaef-445d-8eb2-1384caf207a9 · outbound

This paper cites Space: Locality-aware pro- cessing in heterogeneous memory for personalized recommendations,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Space: Locality-aware pro- cessing in heterogeneous memory for personalized recommendations,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.090173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0ec547d6-6215-4f01-9562-5d2f98689ab5 · outbound

This paper cites Deeprecsys: A system for optimizing end-to-end at-scale neural recommendation inference,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Deeprecsys: A system for optimizing end-to-end at-scale neural recommendation inference,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.076329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 85985198-965f-41c8-999a-8baa9f5dc64f · outbound

This paper cites Rabbit order: Just-in-time parallel reordering for fast graph analysis,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Rabbit order: Just-in-time parallel reordering for fast graph analysis,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.062318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 199f9741-1387-40da-9ca4-bdeae43e7923 · outbound

This paper cites A novel modularity- based discrete state transition algorithm for community detection in networks,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model A novel modularity- based discrete state transition algorithm for community detection in networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.046893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5e201697-7011-4900-87f3-a7b78653e8fe · outbound

This paper cites Fast algorithm for modularity-based graph clustering,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Fast algorithm for modularity-based graph clustering,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.031473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 24caab2f-1e8c-45d8-ad7f-b08200552c36 · outbound

This paper cites Click-through rate prediction,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Click-through rate prediction,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.017519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4f04435b-3a9a-44f7-aaba-aa327007515a · outbound

This paper cites Terabyte click logs,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Terabyte click logs,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:16.003423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 55281007-608d-47aa-8c8d-b7fab46b972d · outbound

This paper cites Display advertising challenge,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Display advertising challenge,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:15.989883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8fec264-871d-4f38-8857-13bff3bcbb56 · outbound

This paper cites Matpower-a matlab power system simulation package: User.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Matpower-a matlab power system simulation package: User

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T16:00:15.380465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a787d1a0-7c39-4ba4-a2f6-e8f51960c842 · outbound

This paper cites Intrusion detection of cyber physical energy system based on multivariate ensemble classification,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Intrusion detection of cyber physical energy system based on multivariate ensemble classification,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:15.966456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d9580da9-253b-4459-9a83-a4f6737153c6 · outbound

This paper cites Torchrec,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Torchrec,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:15.951822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3fb0128e-940a-4b92-9bed-f203690e68c4 · outbound

This paper cites Nvtabular,.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Nvtabular,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:00:15.937374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7786f287-7f44-4e66-8b02-47bed936f2ff · outbound

This paper cites an unresolved cited work.

Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:00:15.923457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 248a2c2b-833d-4674-b0e0-e1299394d957 · inbound

Clustered Federated Learning for Generalizable FDIA Detection in Smart Grids with Heterogeneous Data cites this paper.

Clustered Federated Learning for Generalizable FDIA Detection in Smart Grids with Heterogeneous Data Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:48:02.660562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.