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Paper Citation Record · LEDGER

Accelerating Optimization via Differentiable Stopping Time

As of 9 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 2026-08-09T06:31:02.800959+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
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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

This paper cites Hyperparameter optimization.

Accelerating Optimization via Differentiable Stopping Time Hyperparameter optimization

Reference 4

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

Unavailable: canonical work link unavailable.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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 2026-08-09T06:31:02.800959+00:00.

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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

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 27

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 30

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Source-reported events for the cited work

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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
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Source-reported events for the cited work

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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 2026-08-09T06:31:02.800959+00:00.

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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

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Source-reported events for the cited work

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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
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Source-reported events for the cited work

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

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Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 35

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Source-reported events for the cited work

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

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Accelerating Optimization via Differentiable Stopping Time Unresolved cited work

Reference 36

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:14:19.193468Z digest=sha256:32f7b91902b105256290d797c5af5ba0a5ee75fbba583e0ec0811f282e9b7c6b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:14:19.262570Z digest=sha256:3c6d126764ba3311ebae104b230558d246e04324a2c683c768c996e918c35ad2

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T06:02:40.158866Z digest=sha256:6bbceb5d3f9092cd6cff2bf81339cb73611b75c26e85526e5b27ffd744ed30d2