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Paper Citation Record · LEDGER

Rethinking Neural-based Matrix Inversion: Why can't, and Where can

As of 8 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2506.00642.

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

pith.paper-citation-record.v1
2506.00642 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:07:21.046986Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy19
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a17d9089-4129-460c-a4a9-daef1fddb617 · outbound

This paper cites Almasadeh, Khawla A.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Almasadeh, Khawla A

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:24.359141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.011727Z digest=sha256:7c0b2c315c753eb860eda5b6ee03fd3ad7773d6a210cb82d2048d91afb040950

Observation c8e15363-b5be-4859-84d7-80a2da1babd3 · outbound

This paper cites Sorting out lipschitz function approximation.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Sorting out lipschitz function approximation

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:24.221332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.137823Z digest=sha256:c4549df2566539af36c448c3b67b6cc5aca0ab5f66f121bcf29eca22408fcb96

Observation 345c71f7-8ebb-4fb2-84d8-127958ff9030 · outbound

This paper cites Deep Learning Solution of the Eigenvalue Problem for Differential Operators.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Deep Learning Solution of the Eigenvalue Problem for Differential Operators

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:24.051872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.247292Z digest=sha256:83c1b8630b16f73f2fcd9e866054f109e380c07b7481747eccafd4c9f2b2ce62

Observation 59743d4f-4617-441d-a711-9c9908e50941 · outbound

This paper cites Autm flow: Atomic unrestricted time machine for monotonic normalizing flows.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Autm flow: Atomic unrestricted time machine for monotonic normalizing flows

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:23.837608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.316499Z digest=sha256:4e1f3d179b3c1fed316c947f561fc46446f556d0b61225c92e77dd69f73e9dd0

Observation 236016ff-1dd6-4675-8033-eb4d5c834a30 · outbound

This paper cites Design and analysis of a hybrid gnn-znn model with a fuzzy adaptive factor for matrix inversion.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Design and analysis of a hybrid gnn-znn model with a fuzzy adaptive factor for matrix inversion

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:23.636636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.409785Z digest=sha256:0cbd6e9f508a4e7a1fa48ff44e10e6da4cf884938fc872b4cdc8a3793de4de5f

Observation ead1d00c-403d-411d-8f36-6df7353ad17b · outbound

This paper cites A fuzzy adaptive zeroing neural network model with event-triggered control for time-varying matrix inversion.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can A fuzzy adaptive zeroing neural network model with event-triggered control for time-varying matrix inversion

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:23.490609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.500881Z digest=sha256:24fa312a2eeaaf1b1dc9209ff42c165b9baa7086c2b8e28906f102429c3a0ca8

Observation a5925fcd-e835-43bb-85d7-cb486ca462ff · outbound

This paper cites Dongarra, Iain S.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Dongarra, Iain S

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:23.346857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.605707Z digest=sha256:0c39b275f0bf3c87f3c21ef873ef6b5be573037eae4a47709999aca041df451e

Observation 81aae05c-dc01-48f5-bbb1-b6e37fdac80a · outbound

This paper cites Neural spline flows.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Neural spline flows

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:23.180219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.698484Z digest=sha256:aa88c67cc8448a1c2088fa3c0afa437b6fdd7e97767d94c3fea0bf9672e40f75

Observation 33d75747-4560-4a3c-b0a3-e499ef3fa0bb · outbound

This paper cites Neural network approach to computing matrix inversion.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Neural network approach to computing matrix inversion

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:23.033957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.806530Z digest=sha256:f52995d9ab3b4199851fcd66f13af0078eee1d1e6f5c3cffc9ea4c27b30d9c3c

Observation d88a2826-897b-4a79-9c44-9e9450e7fc69 · outbound

This paper cites From zhang neural network to newton iteration for matrix inversion.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can From zhang neural network to newton iteration for matrix inversion

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:22.868486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.899579Z digest=sha256:43e86066d2c095b7a375cd587bbfab4efd6c8c7c285099221cec07fd64b55f8c

Observation 4580253a-5aa2-4209-8b36-85413ad86d83 · outbound

This paper cites an unresolved cited work.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:07:22.682088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:19.984154Z digest=sha256:382d6677cb5c2a4b35eab476099b8cc1d206e1c53f984eebfd5f8db0196d7ae7

Observation 3c1cbe93-3ec9-452b-8703-af60ee5f89ff · outbound

This paper cites Stanimirović, Panagiotis Tzekis, and Vasilios N.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Stanimirović, Panagiotis Tzekis, and Vasilios N

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:22.509489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.087833Z digest=sha256:d8d853a22031cce266a59875d171f19c5b73c0917fdff95d8b5c52bf61aa6ce0

Observation 8ea59227-806a-4849-ad62-ce8ec712e7d1 · outbound

This paper cites Golub and Charles F.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Golub and Charles F

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:22.321643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.190598Z digest=sha256:db3e2342351b5014739479f75bc23b01b12d7adde6fdd78be7d8e832bef7bdb6

Observation 017385de-6172-4715-89c9-61834763b7b0 · outbound

This paper cites Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion monte carlo like approach.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion monte carlo like approach

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:22.159470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.292962Z digest=sha256:9d4d91dc84c131c7044697f1d7c5eefbd537bed7aca2b149ebe87cdcb654e8a4

Observation c6d3c320-9c1c-410e-a5d5-96b17e23317d · outbound

This paper cites An optimization network for matrix inversion.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can An optimization network for matrix inversion

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:22.018694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.407269Z digest=sha256:747c7c9896110019db49df28bd105b7856ff85cc218b4baea72935efe97571c4

Observation b8415fae-bb1c-463c-9c77-1367e57ec10f · outbound

This paper cites The lipschitz constant of self-attention.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can The lipschitz constant of self-attention

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:21.836165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.496191Z digest=sha256:454ead3e18709515d12a0c02cd92628dfe6e4606e417354984ffcc5944b1868c

Observation da3676ac-7291-42cb-be25-abaee5b7cae1 · outbound

This paper cites Latorre, P.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Latorre, P

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:21.656915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.608980Z digest=sha256:86d8a8295ea3c010f8afb56e3c408a78040aa5faf084969f85fca32416b7e057

Observation 6be6d2c2-9d91-4f7a-9a1f-1bc574027108 · outbound

This paper cites An efficient second-order neural network model for computing the moore–penrose inverse of matrices.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can An efficient second-order neural network model for computing the moore–penrose inverse of matrices

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:21.514839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.735453Z digest=sha256:6fd9ed63c22a3cf07d8cc5c97992b2c2aec2249fe401ac1343319659064b7be8

Observation 0ec1ccd1-373b-4beb-bf95-070441255ead · outbound

This paper cites SGDR: stochastic gradient descent with warm restarts.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can SGDR: stochastic gradient descent with warm restarts

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T12:07:20.849637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:07:20.849637Z digest=sha256:c2d3dee7f4f2ad93621f0b7597e26026435ddd3c503c86937ea77d82e4612ec5

Observation be243719-81c9-4758-b918-0587bfc02954 · outbound

This paper cites Steriti, J.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Steriti, J

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:21.364465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:07:20.935855Z digest=sha256:4daa12f50a0cf961f8461873465219c167e081c540067a3e9bb29b13ce484cbf

Observation 432d354e-951c-4225-8b78-8795aa9aa518 · outbound

This paper cites Virmaux and K.

Rethinking Neural-based Matrix Inversion: Why can't, and Where can Virmaux and K

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:07:21.210907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

No inbound Pith citation observations are available.