Pith. sign in

Paper Citation Record · LEDGER

Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2302.09019.

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

pith.paper-citation-record.v1
2302.09019 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:20:35.286963Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

14
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 03ec70c6-c6ff-4723-8d75-9600d65cc441 · inbound

Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting cites this paper.

Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-12T20:56:16.985524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:56:16.985524Z digest=sha256:664ca1eacb686aa77d78f1584a52f064cad9e1a4fd2f8da5932b6c828d79c8d2

Observation 1856286b-2372-4f7e-89e0-e1924a94bf8e · inbound

Quantum Computing for Energy Management: A Semi Non-Technical Guide for Practitioners cites this paper.

Quantum Computing for Energy Management: A Semi Non-Technical Guide for Practitioners Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 125

Resolution
unresolved
no resolver link, observed 2026-08-12T20:18:06.408432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:18:06.408432Z digest=sha256:f263cf37d884938ca4a28e216404c5516e33d518b5e35afdcb86cef442fd50a3

Observation f2842abd-dee7-4b47-b4fc-c7676d25688b · inbound

No-Free-Lunch Theories for Tensor-Network Machine Learning Models cites this paper.

No-Free-Lunch Theories for Tensor-Network Machine Learning Models Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T20:38:16.787784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:38:16.787784Z digest=sha256:08bb79171e986e3cb628d25f535e40e69ce0d2b5a70a6dfaa18a135644c92bf4

Observation 04bc23d0-7f3c-4321-a51e-e8973a1187b8 · inbound

Derivation of Runge--Kutta Order Conditions via Functional Tree Tensor Networks cites this paper.

Derivation of Runge--Kutta Order Conditions via Functional Tree Tensor Networks Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-22T19:32:00.936482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T19:27:54.397470Z digest=sha256:d8f6f0712789618d87d64b63f3ebee8230b3cd6ab37f24f140ad79502f2bb050

Observation 5e76f715-d7f2-4778-ab7c-f50da733a36c · inbound

Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks cites this paper.

Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:01:56.332166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:01:56.332166Z digest=sha256:9d05759cc5a7aab65ef6b153688aa450f081174121d0bd5d423a3a6374bfd6f3

Observation 5cee59b6-d96c-4741-8e18-1b2d9a485b77 · inbound

Hybrid between biologically and quantum-inspired many-body states cites this paper.

Hybrid between biologically and quantum-inspired many-body states Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:12:15.465482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-19T11:10:33.722038Z digest=sha256:65ea7e0942dd7cfa6340840853bb07ac5b77d8b0cacc311231bbf729e39d1449

Observation 0ef69d80-d47c-4381-b16c-67dc9b40faf6 · inbound

Neuralized Fermionic Tensor Networks for Quantum Many-Body Systems cites this paper.

Neuralized Fermionic Tensor Networks for Quantum Many-Body Systems Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:46:36.929773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T13:45:41.798406Z digest=sha256:a43eace10188a925c527eaa13d160d76a41e0a097637bb94a398666774bbfcaa

Observation 085ed6d4-6c18-49de-9d34-508206212902 · inbound

Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework cites this paper.

Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T19:50:41.299241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:50:41.299241Z digest=sha256:d84f38fa702403c15e97be399a7ce1d32079dda4a4733e21e61e7bf771b178f6

Observation 7da561fd-57d6-4baa-85f2-5be921fefd15 · inbound

Classical Neural Networks on Quantum Devices via Tensor Network Disentanglers: A Case Study in Image Classification cites this paper.

Classical Neural Networks on Quantum Devices via Tensor Network Disentanglers: A Case Study in Image Classification Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:31:44.354799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T18:29:51.375220Z digest=sha256:91c1a60af60b13b0a1d4e1a794785a5ece03874ccfb499a11c4c1efc4f2ab80e

Observation 482f7adc-3bdb-4f4e-bf83-84c42c34050f · inbound

Tensor Network based Gene Regulatory Network Inference for Single-Cell Transcriptomic Data cites this paper.

Tensor Network based Gene Regulatory Network Inference for Single-Cell Transcriptomic Data Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T16:20:35.286963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:20:35.286963Z digest=sha256:807df121d51701084b2d3559c5c6d94aa524195e8303c8911d7833c4f89bca71

Observation b9f507d9-7b91-4246-924f-e85260775ad6 · inbound

A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics cites this paper.

A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 95

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T06:42:26.629798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T06:41:57.161564Z digest=sha256:53f4b54161bdf9d163c4cb4ab9b8d86781d9238bb53afb77a4d1c9e795c34392

Observation 92a0c488-4d6a-4c65-bcf7-9a67b308e09c · inbound

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices cites this paper.

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-03T06:57:48.617730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:57:48.617730Z digest=sha256:4d7f535c7a42959c38072a98ff2bfac42c9dfd093771e5f1169c08024519d977

Observation f14855c3-d58b-4530-b296-76df0dc733e7 · inbound

Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels cites this paper.

Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:36:00.959752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T17:35:10.794244Z digest=sha256:3e0465f71becc74fbcb7b2e73d2281dcf51b624803226b65b715f3a6eb144273

Observation 189de5e8-6e46-40ad-9586-f72c499779c5 · inbound

Quantum-inspired tensor networks in machine learning models cites this paper.

Quantum-inspired tensor networks in machine learning models Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 135

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:50:26.916555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-10T13:50:22.375333Z digest=sha256:0ffe8e0a579dc4ef71bef3f8ffee96d4c8f608d7dbd7efb8ce152a93ec98245c

Observation b7159343-1e51-4dca-be92-50b267f019e8 · inbound

Entanglement is Half the Story: Post-Selection vs. Partial Traces cites this paper.

Entanglement is Half the Story: Post-Selection vs. Partial Traces Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-08T18:28:57.416932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T18:27:32.681510Z digest=sha256:a089ed143a405043804dbef770a4c663ae2685698c88ac5af0de503fbb5a6964

Observation 0d5bcba0-ab55-4cc1-a549-0939ae249597 · inbound

T-GINEE: A Tensor-Based Multilayer Graph Representation Learning cites this paper.

T-GINEE: A Tensor-Based Multilayer Graph Representation Learning Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 53

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T14:23:30.946460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-29T14:15:28.933972Z digest=sha256:1fc3386aea2e631a89b1dbe4a70321b73ec0530f6f20851d3504c0e7664ad23a

Observation 1bbc01b3-62b1-4d90-b9e2-c322846d9255 · inbound

Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Parameter Compression of Deep Neural Networks cites this paper.

Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Parameter Compression of Deep Neural Networks Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-06-29T08:23:15.148164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-29T08:19:56.166378Z digest=sha256:42b72d63e8010b8feb1872888c0915c926fc92ecd862258a074f938c0aa29d1a

Observation 9e7beaf0-f7a8-4325-953d-7d5a199c6556 · inbound

A fast sum-of-Gaussians algorithm for the high-dimensional fractional Fokker-Planck equation cites this paper.

A fast sum-of-Gaussians algorithm for the high-dimensional fractional Fokker-Planck equation Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 49

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T17:55:51.201947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-29T02:59:57.147465Z digest=sha256:bd5f9c8b2c1d5473b432f2bf67ae41f7133174e4b55c6a88d7270ccb024e70ec

Observation db188f74-666e-41b5-9fdd-15e126054dbe · inbound

When AI meets quantum information: A comprehensive review cites this paper.

When AI meets quantum information: A comprehensive review Tensor Networks Meet Neural Networks: A Survey and Future Perspectives

Reference 269

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:46:56.391772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-02T12:41:14.114824Z digest=sha256:c8387552b6de100b1b5440ecd71a82261ad6a2a9a4bd7f8ab4423cac1d4906dd