Paper Citation Record · LEDGER

Accelerating Optimization via Differentiable Stopping Time

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2505.22509.

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

pith.paper-citation-record.v1
2505.22509 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:14:19.262570Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T06:02:40.158866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T06:07:22.629379Z

Reference resolution

37 of 37 outbound references displayed

verified exact3
verified fuzzy27
unresolved6
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad64d91c-e15c-4f0b-9bc6-8d5804ac9072 · outbound

This paper cites Operations research: an introduction, volume 7.

Accelerating Optimization via Differentiable Stopping Time Operations research: an introduction, volume 7

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:25.599531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5bde16a7-456c-460e-ba35-91dda1f09dc8 · outbound

This paper cites A Survey of Large Language Models.

Accelerating Optimization via Differentiable Stopping Time A Survey of Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T13:14:16.646189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc4dd8fc-75fe-4e64-8727-5aab89f5029b · outbound

This paper cites Finance and financial markets.

Accelerating Optimization via Differentiable Stopping Time Finance and financial markets

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:25.464994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc086f64-306d-4f00-a50d-2d49154d374c · outbound

This paper cites Hyperparameter optimization.

Accelerating Optimization via Differentiable Stopping Time Hyperparameter optimization

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:25.320536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 27f6af27-9e8c-4f76-9cde-5cb0ad76bb11 · outbound

This paper cites Learning to optimize: A tutorial for continuous and mixed-integer optimization.

Accelerating Optimization via Differentiable Stopping Time Learning to optimize: A tutorial for continuous and mixed-integer optimization

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:25.193547Z

Source-reported events for the cited work

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Observation 6d46da59-d8db-4dc2-8dc9-dc981dfdeb3e · outbound

This paper cites Problem complexity and method efficiency in optimization.

Accelerating Optimization via Differentiable Stopping Time Problem complexity and method efficiency in optimization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:25.041396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fa890c8f-10cd-4875-beb0-1746132cc4aa · outbound

This paper cites A differential equation for modeling nesterov’s accelerated gradient method: Theory and insights.

Accelerating Optimization via Differentiable Stopping Time A differential equation for modeling nesterov’s accelerated gradient method: Theory and insights

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:24.907238Z

Source-reported events for the cited work

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Observation f75aec49-efba-42e1-a9a4-f3e2c4ac03c6 · outbound

This paper cites Understanding the acceleration phenomenon via high-resolution differential equations.

Accelerating Optimization via Differentiable Stopping Time Understanding the acceleration phenomenon via high-resolution differential equations

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:24.715318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 22beaf0d-1798-425f-a7eb-3edef9920aa9 · outbound

This paper cites Acceleration via symplectic discretiza- tion of high-resolution differential equations.

Accelerating Optimization via Differentiable Stopping Time Acceleration via symplectic discretiza- tion of high-resolution differential equations

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:24.577218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fcbb3121-57cd-4e42-ab9c-f776a9a45dca · outbound

This paper cites A lyapunov analysis for accelerated gradient methods: From deterministic to stochastic case.

Accelerating Optimization via Differentiable Stopping Time A lyapunov analysis for accelerated gradient methods: From deterministic to stochastic case

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:24.431309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2b6e4b9e-c7b0-46de-b043-c2e3fdcd54d4 · outbound

This paper cites Accelerated Natural Gradient Method for Parametric Manifold Optimization.

Accelerating Optimization via Differentiable Stopping Time Accelerated Natural Gradient Method for Parametric Manifold Optimization

Reference 11

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Source-reported events for the cited work

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Observation 7bda6fc5-58c7-4814-91c3-3bdc5b4c1e28 · outbound

This paper cites Efficient and modular implicit differentiation.

Accelerating Optimization via Differentiable Stopping Time Efficient and modular implicit differentiation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:24.302099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 061b4667-7c3c-44a2-8701-ec2b1968cc81 · outbound

This paper cites Nonsmooth implicit differen- tiation for machine-learning and optimization.

Accelerating Optimization via Differentiable Stopping Time Nonsmooth implicit differen- tiation for machine-learning and optimization

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:24.155412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d838e6cf-99ce-4d9d-8810-51511e558895 · outbound

This paper cites Object representations as fixed points: Training iterative refinement algorithms with implicit differentiation.

Accelerating Optimization via Differentiable Stopping Time Object representations as fixed points: Training iterative refinement algorithms with implicit differentiation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:23.982190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1eab9a6b-0350-4c37-8d03-eca6b8939e5b · outbound

This paper cites Implicit differentiation for fast hyperparameter selection in non-smooth convex learning.

Accelerating Optimization via Differentiable Stopping Time Implicit differentiation for fast hyperparameter selection in non-smooth convex learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:23.717779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8f5e1845-aec5-4582-b3db-9a9efb73347c · outbound

This paper cites On training implicit models.

Accelerating Optimization via Differentiable Stopping Time On training implicit models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:23.479318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 87e8a8db-a9e2-4203-bde0-f9589d4c0392 · outbound

This paper cites On implicit bias in overparameterized bilevel optimization.

Accelerating Optimization via Differentiable Stopping Time On implicit bias in overparameterized bilevel optimization

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:23.339284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f0e151e0-8b7e-4eba-8aed-2cf523ec6892 · outbound

This paper cites Revisiting implicit differentiation for learning problems in optimal control.

Accelerating Optimization via Differentiable Stopping Time Revisiting implicit differentiation for learning problems in optimal control

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:23.169796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ba7e964-3fb3-4328-8187-6fea3bc76caf · outbound

This paper cites Learning to optimize: A primer and a benchmark.

Accelerating Optimization via Differentiable Stopping Time Learning to optimize: A primer and a benchmark

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:22.864156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ab5caca-86b2-4c6c-8a69-f18fa9c33af7 · outbound

This paper cites Scalable learning to optimize: A learned optimizer can train big models.

Accelerating Optimization via Differentiable Stopping Time Scalable learning to optimize: A learned optimizer can train big models

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:22.616669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6ea9105d-a39a-4ee0-93d9-b71114290da0 · outbound

This paper cites Training stronger baselines for learning to optimize.

Accelerating Optimization via Differentiable Stopping Time Training stronger baselines for learning to optimize

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:22.364863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 693b1fb6-e3d2-48ab-83f6-2ea24048e900 · outbound

This paper cites Learning to generalize provably in learning to optimize.

Accelerating Optimization via Differentiable Stopping Time Learning to generalize provably in learning to optimize

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:22.061247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c0a3d719-5c36-4b68-8c73-d996c2d407c6 · outbound

This paper cites M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation.

Accelerating Optimization via Differentiable Stopping Time M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:14:19.667408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c6556495-e6ab-45e2-9017-60abc745ce0c · outbound

This paper cites Towards robust learning to optimize with theoretical guarantees.

Accelerating Optimization via Differentiable Stopping Time Towards robust learning to optimize with theoretical guarantees

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:21.806337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 288dc7e8-7427-4ffe-9ee2-f0ccce7db083 · outbound

This paper cites ODE-based Learning to Optimize.

Accelerating Optimization via Differentiable Stopping Time ODE-based Learning to Optimize

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:14:19.548469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2fd7e71a-7ddc-4ae1-8068-cbdf106f9c09 · outbound

This paper cites Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning.

Accelerating Optimization via Differentiable Stopping Time Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:21.488551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 06edf182-d47c-474d-8093-d88715ebe855 · outbound

This paper cites an unresolved cited work.

Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6699bf24-1ba2-40fa-ba48-ac4579e2ab46 · outbound

This paper cites Hoffman, David Pfau, Tom Schaul, and Nando de Freitas.

Accelerating Optimization via Differentiable Stopping Time Hoffman, David Pfau, Tom Schaul, and Nando de Freitas

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:21.031352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f0539375-9d24-4c98-8bc2-5374b7c422c6 · outbound

This paper cites Learning gradient descent: Better generalization and longer horizons.

Accelerating Optimization via Differentiable Stopping Time Learning gradient descent: Better generalization and longer horizons

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:20.845303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ea4a36c8-8afa-49a2-9d29-67c8fbce5691 · outbound

This paper cites an unresolved cited work.

Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aab66efe-ad7a-4049-98d5-e72937b51abd · outbound

This paper cites LIBSVM: A library for support vector machines.

Accelerating Optimization via Differentiable Stopping Time LIBSVM: A library for support vector machines

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:20.714667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3a623a77-9e4e-4c02-a4bd-5c460bfbc8a7 · outbound

This paper cites Online learning rate adaptation with hypergradient descent.

Accelerating Optimization via Differentiable Stopping Time Online learning rate adaptation with hypergradient descent

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:20.542444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a277722c-614f-4e40-a411-d77936011535 · outbound

This paper cites Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent.

Accelerating Optimization via Differentiable Stopping Time Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T13:14:19.004283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d08f747-0931-4da6-a753-716808686f74 · outbound

This paper cites Towards constituting mathematical structures for learning to optimize.

Accelerating Optimization via Differentiable Stopping Time Towards constituting mathematical structures for learning to optimize

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:14:20.392281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 81e65916-21e9-4d62-bff3-712e9752b57e · outbound

This paper cites an unresolved cited work.

Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:14:20.139453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8a08dd60-5237-4091-addf-ad096a032355 · outbound

This paper cites an unresolved cited work.

Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:14:19.994534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71b7aad6-5371-4cb7-a6ba-96aa7b05d96c · outbound

This paper cites Given an initial condition x(t0) = x0 and a fixed stepsize h, we consider the sequence generated by the forward Euler method as xk+1 = xk + hf (xk, tk), t k = t0 + kh.

Accelerating Optimization via Differentiable Stopping Time Given an initial condition x(t0) = x0 and a fixed stepsize h, we consider the sequence generated by the forward Euler method as xk+1 = xk + hf (xk, tk), t k = t0 + kh

Reference 37

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T13:14:19.845351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 08c819f7-f2d2-4ea0-ae41-deb039d51f84 · inbound

Elastic Attention Cores for Scalable Vision Transformers cites this paper.

Elastic Attention Cores for Scalable Vision Transformers Accelerating Optimization via Differentiable Stopping Time

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:07:22.630846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.