Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-08T20:22:19.846227Z
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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
No inbound Pith citation observations are available.