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Paper Citation Record · LEDGER

Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:1805.00915.

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

pith.paper-citation-record.v1
1805.00915 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:07:11.363600Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:47:30.894991Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 033a1e01-5e91-4d06-9408-6538aa5d971d · inbound

Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks cites this paper.

Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-25T12:25:48.183634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T12:22:47.849439Z digest=sha256:a0e2577f460096c4589ade9dc61784dc56360fce48d946f73bed188aeddf7812

Observation 8fd30642-6981-4a8e-9d96-b8995a613049 · inbound

Mean-field limit of particle systems with absorption cites this paper.

Mean-field limit of particle systems with absorption Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:23:59.955881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T06:21:57.750645Z digest=sha256:e4c309e557fe9f8c99ebe5011255ec710ecbf68a23d389690a7bcee8fdf1185b

Observation 543efb9a-b1c8-4957-bd12-3004f3947de5 · inbound

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models cites this paper.

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 211

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:00:21.381385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T23:00:20.720030Z digest=sha256:0c411bbb3c9b0b26e69eb8fc3078f3fc55502999e46edc893561e404febeebae

Observation edbdb1df-1cb0-4048-a220-b85eb11f7af0 · inbound

Mirror Descent-Ascent for mean-field min-max problems cites this paper.

Mirror Descent-Ascent for mean-field min-max problems Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:48:53.049650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T03:47:22.184621Z digest=sha256:35da022a11411e181e249f206e86ed207bd577e96a2712d0127962c46a5422e4

Observation 26011c8a-0f6d-4fad-956d-580c700b52ab · inbound

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact cites this paper.

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 189

Resolution
unresolved
no resolver link, observed 2026-08-06T21:07:11.363600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:07:11.363600Z digest=sha256:87bb8e5aa1af68d5dcf303e91f29ec9560628ba638d15e107ffb615f362a674b

Observation ccdab250-9f6c-4c42-b100-9ceba63b2a8c · inbound

Genericity of Polyak-Lojasiewicz Inequalities for Entropic Mean-Field Neural ODEs cites this paper.

Genericity of Polyak-Lojasiewicz Inequalities for Entropic Mean-Field Neural ODEs Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:23.541601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:32:23.541601Z digest=sha256:65b44d91fe87674d43b12bb16063adf5c9ebcbf4a02769fb48f3dfdf1c26a523

Observation 8a0256a6-2366-49b5-9d22-bab7bbaccddd · inbound

Limit Theorems for Stochastic Gradient Descent in High-Dimensional Single-Layer Networks cites this paper.

Limit Theorems for Stochastic Gradient Descent in High-Dimensional Single-Layer Networks Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:55:38.129353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T01:54:21.607337Z digest=sha256:8d8a05cdb60b9d52139a9c8ea8378294b35794eabaf9c506cf21ade17d4b9251

Observation 14f47da4-a70a-41c4-bb92-2d9732d5c14c · inbound

Limit Theorems for Stochastic Gradient Descent in High-Dimensional Single-Layer Networks cites this paper.

Limit Theorems for Stochastic Gradient Descent in High-Dimensional Single-Layer Networks Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T00:22:01.242931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:22:01.242931Z digest=sha256:f1e6cbd0e7c4a56bf0ff5b07d362717a48fa68e0dcded32379bb5be7b9f61003

Observation 0b93df28-e0df-4f55-9a62-1b013180fb02 · inbound

A unified perspective on fine-tuning and sampling with diffusion and flow models cites this paper.

A unified perspective on fine-tuning and sampling with diffusion and flow models Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 133

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:31:21.483348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T19:43:42.331642Z digest=sha256:157a8e7af81cb30116180031057f622014dcffd92b2e8934f66f913825d65707

Observation 7a4f8f42-66b0-48d1-ba0a-ce89304480d4 · inbound

Uniform-in-Time Weak Propagation-of-Chaos in Shallow Neural Networks cites this paper.

Uniform-in-Time Weak Propagation-of-Chaos in Shallow Neural Networks Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T04:31:03.665978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T04:30:48.081597Z digest=sha256:7232568ef729ccd43fde11de72839144c10a79251f6ee8e2b72dede8a80f8612

Observation 8aaa421b-089c-4053-b0fd-25174f64a6f3 · inbound

A Theory on Flow Matching with Neural Networks cites this paper.

A Theory on Flow Matching with Neural Networks Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 234

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T00:47:30.896984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T16:59:34.084575Z digest=sha256:fd838161086e77e9af12d6910d448b91fc3fb1609d07217ffa9ed86eec0bf0ef

Observation f5a7887c-077e-4a69-aedf-2ae61185b924 · inbound

Geometric Dyson Brownian Motions and the Free Log-Normal Limit for a Non-Square Gaussian Matrix Product cites this paper.

Geometric Dyson Brownian Motions and the Free Log-Normal Limit for a Non-Square Gaussian Matrix Product Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-07-01T12:55:43.881081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T01:42:14.145227Z digest=sha256:a502a663e7edd92094386d8b9c177e355dce94f5e96d08f269d616d05776bb53

Observation 47725617-9b45-44d7-bcd4-5f1fa95b24fe · inbound

Geometric Dyson Brownian Motions and the Free Log-Normal Limit for a Non-Square Gaussian Matrix Product cites this paper.

Geometric Dyson Brownian Motions and the Free Log-Normal Limit for a Non-Square Gaussian Matrix Product Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-02T09:36:51.740009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:36:51.740009Z digest=sha256:55134ecbc5176a08f39fbb6a3248c2fb093da5b582947f5f0eaec820c914ecb8

Observation 3ffb25da-2f5d-46eb-b9b6-1caba77633bf · inbound

Implicit Bias of SGD in Multivariate ReLU Networks: Effective Width Collapse cites this paper.

Implicit Bias of SGD in Multivariate ReLU Networks: Effective Width Collapse Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Reference 256

Resolution
unresolved
no resolver link, observed 2026-07-12T01:11:50.444218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T01:11:50.444218Z digest=sha256:436d5e7b371800e054a273c7f9ba75a55861e3ce64d5080fc41433628169b282