Paper Citation Record · LEDGER

Adaptive control mechanisms in gradient descent algorithms

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2508.19100.

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

pith.paper-citation-record.v1
2508.19100 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:03:57.644468Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

18 of 18 outbound references displayed

verified exact1
verified fuzzy16
unresolved1
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a1465c5d-3c07-4e3c-85f1-74fc237098e0 · outbound

This paper cites Borrelli, A.

Adaptive control mechanisms in gradient descent algorithms Borrelli, A

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:01.444818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c80861a-84db-42a0-8c93-7035c29d50d0 · outbound

This paper cites Convex q learning in a stochastic environment,.

Adaptive control mechanisms in gradient descent algorithms Convex q learning in a stochastic environment,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:01.226268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f1f7c09c-af12-40ef-86a2-cb6747d3d3b0 · outbound

This paper cites Convex optimization for shallow neural networks,.

Adaptive control mechanisms in gradient descent algorithms Convex optimization for shallow neural networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:01.011427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dfb289b8-3737-4049-b661-0e2e7c3c25a8 · outbound

This paper cites Optimization algorithm synthesis based on integral quadratic constraints: A tutorial,.

Adaptive control mechanisms in gradient descent algorithms Optimization algorithm synthesis based on integral quadratic constraints: A tutorial,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:00.760877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 017d4ec0-4ff4-45e8-a77d-16ef2000de22 · outbound

This paper cites Toward a systems theory of algorithms,.

Adaptive control mechanisms in gradient descent algorithms Toward a systems theory of algorithms,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:00.526744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ccbffcf0-e9f7-44e1-8a2c-be782eb480b1 · outbound

This paper cites Acceleration by stepsize hedging: Silver stepsize schedule for smooth convex optimization,.

Adaptive control mechanisms in gradient descent algorithms Acceleration by stepsize hedging: Silver stepsize schedule for smooth convex optimization,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:00.299237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 585aa806-d203-4f5a-90c8-e73cd1be009d · outbound

This paper cites Provably faster gradient descent via long steps,.

Adaptive control mechanisms in gradient descent algorithms Provably faster gradient descent via long steps,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:04:00.080943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e47ff7a7-9e2e-494f-b078-056deb6f3760 · outbound

This paper cites Anytime Acceleration of Gradient Descent.

Adaptive control mechanisms in gradient descent algorithms Anytime Acceleration of Gradient Descent

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-05T16:03:57.991430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7ad196c7-fb11-4ede-a1e7-537122eafabd · outbound

This paper cites Adaptive proximal algorithms for convex optimization under local lipschitz continuity of the gradient,.

Adaptive control mechanisms in gradient descent algorithms Adaptive proximal algorithms for convex optimization under local lipschitz continuity of the gradient,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:59.863838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08939915-5235-4b54-b2a3-f1f13f8a580c · outbound

This paper cites On the convergence of adaptive first order methods: proximal gradient and alternating min- imization algorithms,.

Adaptive control mechanisms in gradient descent algorithms On the convergence of adaptive first order methods: proximal gradient and alternating min- imization algorithms,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:59.621713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0b22bf24-f572-4751-ba85-da761e4975f7 · outbound

This paper cites Adaptive proximal gradient method for convex optimization,.

Adaptive control mechanisms in gradient descent algorithms Adaptive proximal gradient method for convex optimization,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:59.494113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aadfddaa-83e7-45ef-a713-790097b050a8 · outbound

This paper cites Online convex programming and regularization in adaptive control,.

Adaptive control mechanisms in gradient descent algorithms Online convex programming and regularization in adaptive control,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:59.301022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ae405b21-84df-43be-92d8-df450d3891ff · outbound

This paper cites Nesterov, Introductory Lectures on Convex Optimization: A Basic Course.

Adaptive control mechanisms in gradient descent algorithms Nesterov, Introductory Lectures on Convex Optimization: A Basic Course

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:59.123703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d67f0325-a4d3-4df9-91ff-e63556214110 · outbound

This paper cites An elementary approach to tight worst case complexity analysis of gradient based methods,.

Adaptive control mechanisms in gradient descent algorithms An elementary approach to tight worst case complexity analysis of gradient based methods,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:58.976208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a9905607-4316-448a-9827-fd70360c5802 · outbound

This paper cites Directional smoothness and gradient methods: Convergence and adaptivity,.

Adaptive control mechanisms in gradient descent algorithms Directional smoothness and gradient methods: Convergence and adaptivity,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:58.786234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5959ab96-702f-489d-909d-8d1e77d1901c · outbound

This paper cites Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes.

Adaptive control mechanisms in gradient descent algorithms Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T16:03:57.423825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2474627-2a52-4334-a621-ca0e872922ac · outbound

This paper cites Online convex optimization and integral quadratic constraints: An automated approach to regret analysis,.

Adaptive control mechanisms in gradient descent algorithms Online convex optimization and integral quadratic constraints: An automated approach to regret analysis,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:58.585638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6ee34f9a-f52f-43df-ac38-d6f7df7b3b57 · outbound

This paper cites Beck, First-Order Methods in Optimization.

Adaptive control mechanisms in gradient descent algorithms Beck, First-Order Methods in Optimization

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:03:58.252768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.