Paper Citation Record · LEDGER

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models

As of 17 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2505.11664.

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

pith.paper-citation-record.v1
2505.11664 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:58:55.348402Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:25:16.465309Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact1
verified fuzzy13
unresolved22
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dc8accb0-e87d-4691-96f4-c95112fefc7c · outbound

This paper cites A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.093409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a052f10-b2fe-423d-9bb3-41b0312bf1b8 · outbound

This paper cites Convex optimization.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Convex optimization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.102963Z

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Unavailable: canonical work link unavailable.

Observation 36bed00a-a8aa-4b1d-9e5b-037404e57dfd · outbound

This paper cites Spectral compressed sensing via structured matrix completion.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Spectral compressed sensing via structured matrix completion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.199723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 06c6b081-df56-4ae3-87e3-37786a5ea7b0 · outbound

This paper cites On Feature Learning in Neural Networks with Global Convergence Guarantees.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models On Feature Learning in Neural Networks with Global Convergence Guarantees

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.123804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 956a141d-acd8-4d1b-b971-1cd7efc48c42 · outbound

This paper cites On the global convergence of gradient descent for over-parameterized models using optimal transport.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models On the global convergence of gradient descent for over-parameterized models using optimal transport

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.129982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8a7cc03-19f1-439c-8c33-091b0f0fca1d · outbound

This paper cites On lazy training in differentiable programming.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models On lazy training in differentiable programming

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.136766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 223dda5f-58cc-4e4d-b1f4-c49627cddc91 · outbound

This paper cites Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.143175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8581951c-69e5-468e-83bf-7a4dda99af51 · outbound

This paper cites Overparameterization of deep resnet: Zero loss and mean-field analysis.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Overparameterization of deep resnet: Zero loss and mean-field analysis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.153758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f93e3d4-6101-423d-99cd-7ff5b6dd4564 · outbound

This paper cites Width provably matters in optimization for deep linear neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Width provably matters in optimization for deep linear neural networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.132635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f53f6145-ad48-4472-a56c-40f79a9d1e4e · outbound

This paper cites Algorithmic regularization in learning deep homogeneous models: Layers are automatically balanced.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Algorithmic regularization in learning deep homogeneous models: Layers are automatically balanced

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.110813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e171d16b-a7bf-4937-be0d-001ef3ed2cbc · outbound

This paper cites Gradient Descent Provably Optimizes Over-parameterized Neural Networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.168298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 253b037f-7e30-4e78-9490-141aaa301a13 · outbound

This paper cites Gradient descent provably solves nonlinear tomographic reconstruction.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Gradient descent provably solves nonlinear tomographic reconstruction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.091473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ccd09bf8-8bda-43c5-b310-ca9c14dba196 · outbound

This paper cites Learning dynamics of deep matrix factorization beyond the edge of stability.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Learning dynamics of deep matrix factorization beyond the edge of stability

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.069418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b1aeff95-a250-4330-9a53-81764012fdcb · outbound

This paper cites Implicit regularization of discrete gradient dynamics in linear neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Implicit regularization of discrete gradient dynamics in linear neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:56.047226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94e450f1-8599-4ce9-acb1-f96c702e815f · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Understanding the difficulty of training deep feedforward neural networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.196187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73e3b003-7fab-4b74-a865-2c71c1b156c1 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, 2015.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, 2015

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.202294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 851289cd-95fb-47e9-9fdd-45c715637d1c · outbound

This paper cites Deep residual learning for image recognition.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Deep residual learning for image recognition

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.213813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31bf8418-ad56-40b0-aef7-a2a5c29af3c8 · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Neural tangent kernel: Convergence and generalization in neural networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.220096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afdd8ae9-129c-45e0-9e31-cf4af9932455 · outbound

This paper cites Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition, 2020.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition, 2020

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:55.959418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7cecdcd8-b1bf-41b0-8714-98e32730dd97 · outbound

This paper cites Matrix factorization techniques for recommender systems.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Matrix factorization techniques for recommender systems

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.232271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05b16bb5-6a8a-4415-8cb1-73527d25df3d · outbound

This paper cites Wide neural networks of any depth evolve as linear models under gradient descent.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Wide neural networks of any depth evolve as linear models under gradient descent

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.238555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6afe3676-1505-48c4-b114-f37a88b45ba6 · outbound

This paper cites Loss landscapes and optimization in over-parameterized non-linear systems and neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Loss landscapes and optimization in over-parameterized non-linear systems and neural networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.244939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fd9b5e7-53a9-4da3-81d3-44fe71515d5a · outbound

This paper cites A mean field view of the landscape of two-layer neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models A mean field view of the landscape of two-layer neural networks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.250687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96e5b7d0-d01a-4d3b-86e6-a15d89b81656 · outbound

This paper cites On the explicit role of initialization on the convergence and implicit bias of overparametrized linear networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models On the explicit role of initialization on the convergence and implicit bias of overparametrized linear networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:55.860324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 51fa7623-a15c-4844-8934-5a57f8968c01 · outbound

This paper cites Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.263712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d9b9093-eb98-4809-8956-b865bfffe1e5 · outbound

This paper cites On the convergence of gradient flow on multi-layer linear models.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models On the convergence of gradient flow on multi-layer linear models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:55.834479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7eb8f73b-f146-4f4d-ba45-d318a1e9dd93 · outbound

This paper cites Convergence of gradient descent for learning linear neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Convergence of gradient descent for learning linear neural networks

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:58:55.466939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 64cfcfa8-d746-4b01-bb33-cdd9bb5453b7 · outbound

This paper cites Global convergence of deep networks with one wide layer followed by pyramidal topology.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Global convergence of deep networks with one wide layer followed by pyramidal topology

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.291716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f371bb70-e562-4eb4-90e9-01d78a83ad6a · outbound

This paper cites Gradient methods for the minimisation of functionals.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Gradient methods for the minimisation of functionals

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:55.800333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e3e707bc-7fb9-4ac5-9ee3-67cc2ef0ac8f · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.308511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f1181db-b87f-4d8e-ae98-a872b4e1399a · outbound

This paper cites Mean field analysis of neural networks: A law of large numbers.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Mean field analysis of neural networks: A law of large numbers

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.316795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eaf94c2-daf8-4862-a101-556370616dfe · outbound

This paper cites Understanding the dynamics of gradient flow in overparameterized linear models.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Understanding the dynamics of gradient flow in overparameterized linear models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:55.762828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 266fb370-78cb-4933-9bd5-e3640bc0ad32 · outbound

This paper cites Tensor2Tensor for Neural Machine Translation.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Tensor2Tensor for Neural Machine Translation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.329507Z

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Unavailable: canonical work link unavailable.

Observation cd01c3ab-011f-4929-9be5-71cd6f4bbf3e · outbound

This paper cites High-dimensional probability: An introduction with applications in data science, volume 47.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models High-dimensional probability: An introduction with applications in data science, volume 47

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.335484Z

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Unavailable: canonical work link unavailable.

Observation b94095eb-8f34-4ba9-8876-c67e6935574c · outbound

This paper cites Linear convergence of gradient descent for finite width over-parametrized linear networks with general initialization.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Linear convergence of gradient descent for finite width over-parametrized linear networks with general initialization

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:58:55.711875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c18ad132-23f9-45f1-b785-4a94da9df476 · outbound

This paper cites write newline.

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models write newline

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T20:58:55.348402Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 39c2e58c-ee65-4b5d-82ab-0899222b0a13 · inbound

The Optimization Landscape of Carath\'eodory Decomposition of Toeplitz Covariances cites this paper.

The Optimization Landscape of Carath\'eodory Decomposition of Toeplitz Covariances A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T00:25:16.465309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.