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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 23 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.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:00:15.397589Z

measured 51 of 51 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 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
  • verified fuzzy35
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

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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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.

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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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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.

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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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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.

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:14.740811Z digest=sha256:d53b81c31384899b9451e5b6dc1e1242636e5cc80f2c66ceaa2d45f1bdc69e6e

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

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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.

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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

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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.

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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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verified fuzzy
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Source-reported events for the cited work

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

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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

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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.

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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 2026-08-23T06:30:58.430688+00:00.

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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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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.

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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.

source=pdf_text observed=2026-08-06T16:00:15.230594Z digest=sha256:e54de144c47432185cf033d784f28dafcefedddaa51a1858750a2006a2a8cb94

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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unresolved
raw_fallback, observed 2026-08-06T16:00:16.316097Z

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.

source=pdf_text observed=2026-08-06T16:00:15.234938Z digest=sha256:ebfec52563ed2263b25f11abce51a8be2cd0eeb76a1c8450951c907efb66e305

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

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.239969Z digest=sha256:bf61facd00d3bf94bb0ab0e7c939d74f24b4c088e581ce1ef90ba20931d50164

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

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.243890Z digest=sha256:902fe448a0960155fff29fc8d14d7f6f49560e6baa85e4feb9471e67680dd409

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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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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.

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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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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.

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.261170Z digest=sha256:1ad11c2442aae5c639175e4fa43059c2d42ba9a5e80d3f6b9ea15234f38e6d13

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

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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.

source=pdf_text observed=2026-08-06T16:00:15.265560Z digest=sha256:389c6bce76d352a95c4c737debad73b9affbe11a40fa514b35ab1e2d6f19ca05

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

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.269771Z digest=sha256:f5ad1c9835f61991df6885994bce6b3bf3a7bff6d3b4c6255293b0919d2016fa

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

Unavailable: canonical work link unavailable.

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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

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.281380Z digest=sha256:b41131b7c42b1f541f34db9cb991780994ab75cb5981d027354146947a6d7eb1

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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 2026-08-23T06:30:58.430688+00:00.

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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

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.298470Z digest=sha256:7131d92f0df1ca0312703518e00cba720dda8cc96bf50e2259d8c271e9112f0f

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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.

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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

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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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.320156Z digest=sha256:ce9f2d252845836f9b0b95e8b5d4974adcc98ddea42f4d8d29896cbac16a5de6

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.324090Z digest=sha256:b4c0abb871edb287b5c0cfda6a1ff87607cf5192e9d0776bce929f3fd7b8f039

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

Resolution
unresolved
no resolver link, observed 2026-08-06T16:00:15.328142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:00:15.328142Z digest=sha256:db0038109b12de07dce0f8a3a0b14b87fc963d8e432d001498cd060bea4382b8

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.332724Z digest=sha256:bb7039ce70df876bc514d5ce18937be365fa21c7e47b6d4b7dfb5695b8d08330

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.337803Z digest=sha256:5f35c68319064428e7979467f7151e7b55612886dc4c91be379e4718ce56a6d0

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.342049Z digest=sha256:6a91054fc278de7227c035a4eb34a20805509d7b6e758f6f023fc089c4c7d81a

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.346131Z digest=sha256:974c97d00ed1f2508c2df3910e86656fb044dd1ce1793e93f891d3e052d7b04b

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.351038Z digest=sha256:5a5d5f52afcc18aada7676f68260786a7e31e4d75178496c54ded9576854ee92

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.355231Z digest=sha256:1438bed434c18a9676f3feae7b44e357a17e2fd3ff42d30a33526c9bacded6dc

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.359503Z digest=sha256:f573b35a5254338fbea24e3ea7baae5e08aa228e3390cecedf757c5d79569528

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.363791Z digest=sha256:f85992771e25aa85e67a3359a2cc7018af88a270f60d82860d80393a91e87dbe

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.367687Z digest=sha256:cc38dc4d09635c1dccd3d74fde10ee0d8f3930abba0a831a042d69a7fbaf39b3

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.372189Z digest=sha256:8812405645e9633696905faba49505ebd10e6dd3de2a831fc6c16ae2dec82364

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.376394Z digest=sha256:65e4a243a6d9b902e7025bc1eb480d5a523a05ab2c4e114a6f4dd4a511bab968

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.

source=pdf_text observed=2026-08-06T16:00:15.380465Z digest=sha256:b164fdf70dfc4c8ad90e11f1f480f342e1217ccfef39cf77a01892b14d04a5f5

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.384338Z digest=sha256:131be2c58b0d2f74d37167ab810f1a37b6085540045de0b2b931871c8c161c4f

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.388658Z digest=sha256:1d99692571012e8308cac70b63abfe76e0e6e16f8053c2c56bd8238f0ba148a5

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.392685Z digest=sha256:f7c8c3e544c34e6ed55c81d902a64af2307caf266d876dc46000c4f7cc1390c6

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T16:00:15.397589Z digest=sha256:8ca2b34dc3ba74d9c9edc24658155b2cccb4a70b6388c7e98a09540c036b573c

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T15:48:02.551884Z digest=sha256:aea3a4ee0aaa8824dd4cb3d85e88ea78ee29d7ff810a900fc703fb1e90dc1c6b