Paper Citation Record · LEDGER

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points

As of 22 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.05947.

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

pith.paper-citation-record.v1
2607.05947 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T20:22:19.846227Z

measured 31 of 31 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 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

31 of 31 outbound references displayed

verified exact2
verified fuzzy28
unresolved1
parse uncertain0
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External citation measurements

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Outbound references

Observation ea0d01bb-e3e3-4cb5-a02f-55bca1b6abe6 · outbound

This paper cites On an algorithm for the minimization of convex functions.Soviet Mathematics Doklady, 6:286–290, 1965.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points On an algorithm for the minimization of convex functions.Soviet Mathematics Doklady, 6:286–290, 1965

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.519492Z

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.

Observation a5bff768-c032-416c-87a0-ad47f30d9aaa · outbound

This paper cites Oracle complexity of second-order methods for finite-sum problems.International Conference on Machine Learning, 2017.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Oracle complexity of second-order methods for finite-sum problems.International Conference on Machine Learning, 2017

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.515646Z

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.

Observation 9ec10040-6ca7-49e3-93b7-5f0dde537b89 · outbound

This paper cites Oracle complexity of second-order methods for smooth convex optimization.Mathematical Programming, 178(1):327–360.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Oracle complexity of second-order methods for smooth convex optimization.Mathematical Programming, 178(1):327–360

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.509881Z

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.

Observation d66ca4b7-b4d4-4706-8e7b-9251a3794650 · outbound

This paper cites Sur les opérations dans les ensembles abstraits et leur application aux équations intégrales.Fundamenta mathematicae, 3(1):133–181, 1922.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Sur les opérations dans les ensembles abstraits et leur application aux équations intégrales.Fundamenta mathematicae, 3(1):133–181, 1922

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.511770Z

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.

Observation e3644ba8-1b5e-46d8-bacd-ab9f007ee0c4 · outbound

This paper cites Springer, 2017.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Springer, 2017

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.517609Z

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.

Observation f17f301f-999c-4ee4-9ff7-2f1503670b77 · outbound

This paper cites Convex until proven guilty.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Convex until proven guilty

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.506977Z

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.

Observation 76031c38-b456-41bf-8071-70d09f33e211 · outbound

This paper cites Accelerated methods for nonconvex optimization.SIAM Journal on Optimization, 28(2):1751–1772, 2018.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Accelerated methods for nonconvex optimization.SIAM Journal on Optimization, 28(2):1751–1772, 2018

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.534118Z

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.

Observation cab6f59a-481d-4e29-b8b6-502c3c25552a · outbound

This paper cites Lower bounds for finding stationary points I.Mathematical Programming, 184(1):71–120, 2020.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Lower bounds for finding stationary points I.Mathematical Programming, 184(1):71–120, 2020

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.502853Z

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.

Observation 77eb1da4-28c9-4fcb-8693-dd4fc3b39b14 · outbound

This paper cites Lower bounds for finding stationary points II: First-order methods.Mathematical Programming, 185(1):315–355, 2021.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Lower bounds for finding stationary points II: First-order methods.Mathematical Programming, 185(1):315–355, 2021

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.528132Z

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.

Observation eda8c39b-7d96-4ca8-8338-667cdf41e297 · outbound

This paper cites Adaptive cubic regularisation methods for unconstrained optimization.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Adaptive cubic regularisation methods for unconstrained optimization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.523781Z

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.

Observation f4b46a79-af09-4f40-9d4f-9a3062998aa0 · outbound

This paper cites Optimal Acceleration for Proximal Minimization of the Sum of Convex and Strongly Convex Functions.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Optimal Acceleration for Proximal Minimization of the Sum of Convex and Strongly Convex Functions

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:25:37.286337Z

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.

Observation 4ccd098a-5e21-4eec-b2b9-1c3b54b9b59d · outbound

This paper cites Optimal error bounds for non-expansive fixed-point iterations in normed spaces.Mathematical Programming, 199(1):343–374, 2023.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Optimal error bounds for non-expansive fixed-point iterations in normed spaces.Mathematical Programming, 199(1):343–374, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.530099Z

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.

Observation 385934bc-5790-488d-aa61-428965d4cbea · outbound

This paper cites Halpern iteration for near-optimal and parameter-free monotone inclusion and strong solutions to variational inequalities.Conference on Learning Theory.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Halpern iteration for near-optimal and parameter-free monotone inclusion and strong solutions to variational inequalities.Conference on Learning Theory

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.541031Z

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.

Observation 5a57ce98-ddec-4fd5-ab31-8812946138f2 · outbound

This paper cites The exact information-based complexity of smooth convex minimization.Journal of Complexity, 39:1–16, 2017.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points The exact information-based complexity of smooth convex minimization.Journal of Complexity, 39:1–16, 2017

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.525789Z

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.

Observation 67eceb37-e4b6-4269-9ed3-02923d7b2fb9 · outbound

This paper cites On the oracle complexity of smooth strongly convex minimization.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points On the oracle complexity of smooth strongly convex minimization

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.560455Z

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.

Observation 73af25f9-bd7a-49d3-a3b5-15ad68e8a4f6 · outbound

This paper cites Computer-assisted design of accelerated composite optimization methods: OptISTA.Mathematical Programming, pages 1–109, 2025.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Computer-assisted design of accelerated composite optimization methods: OptISTA.Mathematical Programming, pages 1–109, 2025

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.556083Z

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.

Observation efc685dd-191e-4278-9ab1-4e667e824d6e · outbound

This paper cites Accelerated gradient descent escapes saddle points faster than gradient descent.Conference on Learning Theory, 2018.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Accelerated gradient descent escapes saddle points faster than gradient descent.Conference on Learning Theory, 2018

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.565040Z

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.

Observation 0a44bbab-b3ca-4310-9346-8aa2e35c1f31 · outbound

This paper cites SIAM, 1995.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points SIAM, 1995

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.564069Z

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.

Observation 5484d2f6-e988-498b-a7ed-cf55d3ec5794 · outbound

This paper cites Accelerated proximal point method for maximally monotone operators.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Accelerated proximal point method for maximally monotone operators

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.551450Z

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.

Observation faf78a50-2457-4f03-bda7-2af016843064 · outbound

This paper cites The first optimal acceleration of high-order methods in smooth convex optimization.Neural Information Processing Systems, 2022.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points The first optimal acceleration of high-order methods in smooth convex optimization.Neural Information Processing Systems, 2022

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.553945Z

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.

Observation f3be8311-f4fe-4a4b-8924-dd368c11173f · outbound

This paper cites an unresolved cited work.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-07-08T20:25:37.558203Z

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.

Observation 69ae834a-5b17-4ae3-a1e2-bd9e0534b27b · outbound

This paper cites On the convergence rate of the halpern-iteration.Optimization letters, 15(2):405– 418, 2021.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points On the convergence rate of the halpern-iteration.Optimization letters, 15(2):405– 418, 2021

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.546038Z

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.

Observation c247fed3-5373-40e4-a4c6-7724fa37de9a · outbound

This paper cites Wiley-Interscience, 1983.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Wiley-Interscience, 1983

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.538226Z

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.

Observation c603f93c-4f30-43c9-9a33-cbd37ead55ac · outbound

This paper cites Springer.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Springer

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.562274Z

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.

Observation e5b8619e-e9c0-46f7-bf96-2fdeabeea0a7 · outbound

This paper cites Cubic regularization of Newton method and its global performance.Mathematical Programming, 108(1):177–205, 2006.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Cubic regularization of Newton method and its global performance.Mathematical Programming, 108(1):177–205, 2006

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.504837Z

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.

Observation c438f64e-7456-4af3-866b-1a1c3fddf264 · outbound

This paper cites Location of the maximum on unimodal surfaces.Journal of the ACM (JACM), 12(3):395–398, 1965.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Location of the maximum on unimodal surfaces.Journal of the ACM (JACM), 12(3):395–398, 1965

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.531926Z

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.

Observation 06217a58-3203-4ec9-8aa6-fa2fb1106cd4 · outbound

This paper cites SIAM.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points SIAM

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.521809Z

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.

Observation 6506ba09-e27c-417a-a1e5-a6053c88d549 · outbound

This paper cites Exact optimal accelerated complexity for fixed-point iterations.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Exact optimal accelerated complexity for fixed-point iterations

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.513511Z

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.

Observation 2a32fa36-d5e4-4dc9-8ccb-f2fba37d4686 · outbound

This paper cites Memoire sur la theorie des equations aux derivees partielles et la methode des approximations successives.Journal de Mathématiques pures et appliquées, 6:145–210, 1890.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Memoire sur la theorie des equations aux derivees partielles et la methode des approximations successives.Journal de Mathématiques pures et appliquées, 6:145–210, 1890

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.548932Z

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.

Observation b5242e65-cabd-445e-b43a-78a14f5176cd · outbound

This paper cites A first order method for solving convex bilevel optimization problems.SIAM Journal on Optimization, 27(2):640–660, 2017.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points A first order method for solving convex bilevel optimization problems.SIAM Journal on Optimization, 27(2):640–660, 2017

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T20:25:37.543571Z

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.

Observation 4ec1488f-8467-4a26-ac3e-d27fc76f1fcf · outbound

This paper cites Sharp First-Order Lower Bounds for Higher-Order Smooth Nonconvex Optimization.

Higher-Order Derivatives Do Not Accelerate the Computation of Fixed Points Sharp First-Order Lower Bounds for Higher-Order Smooth Nonconvex Optimization

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-07-08T20:25:37.283270Z

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.

Pith citing papers

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