Pith. sign in

Paper Citation Record · LEDGER

Accelerating Optimization via Differentiable Stopping Time

As of 17 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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:16.548691Z digest=sha256:df6a20147d6b3e542798f12bd66746e6fde956289577bf04f250ace494cfe6d8

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.

source=pdf_text observed=2026-08-07T13:14:16.646189Z digest=sha256:bc53619195a68814e2b0dba6c6dcd5a729035de6841d37c11b2abae04f5159f5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:16.751375Z digest=sha256:251c828e83fba56441c5349ffc5a7674f1de1a2de3b6c85c6535499affe9c739

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:16.863831Z digest=sha256:aa637994e8b4beff877aa9fa00dbe3c2105a34e49a6bf068b685a449e303f1ed

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

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:16.939813Z digest=sha256:85b0d68c7c59497c1efecaacd58802126701322369a9f7fb5628597e22d67b89

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.006322Z digest=sha256:d776c73b4da2aeeb1044bb56da7461f164438e07f90c1ad295251872954558da

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

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.075812Z digest=sha256:e6e63a20609e9a5c8e339fc83bdb6365d635a3f8408ae292f493db28ba0182c4

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.118207Z digest=sha256:a02770699b0f16318e75e0d1e136082f93f2b20961d876e6aecb15a0e3b90639

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.232980Z digest=sha256:436ebad4f0375a701b70dd67d3f25b466c926e4dd1ad83c073bbf5e47f201e91

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.308211Z digest=sha256:d047d248b1e5c0a7601664d6009b0f57bfdf49a41d8dd3d88c52210b41485bbe

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

Resolution
unresolved
no resolver link, observed 2026-08-07T13:14:17.378321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:14:17.378321Z digest=sha256:3e4697e4e3964104cab5eba8570deb40a81373397ba5c6f6d87954478e43a7e9

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.441447Z digest=sha256:2a630273b76ce77112c78bb04f67ae008ee43bad4f756f6329ff06788b552c12

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.492720Z digest=sha256:12e9863eda08402b35b31e66a5aedd76138edc13bb5fef88996c34ef42ded1bf

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.550453Z digest=sha256:e4a6910bf34dee9737d7d5ea14883b755394fd708060c51cfe98f8d0fef5f7f5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.608408Z digest=sha256:c242f7f7bdc28a79bf7100c1531fb851e81ba8df03938e1c0801473f2addcccc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.680355Z digest=sha256:3f3bb9237b77298a601f6f6fed99fa60d43e5a4626fa4e2444adf33d76063129

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.762070Z digest=sha256:19c2463efb02dd4b83e6912e8ebf2f47fa781a3a251047f8c0ae09f3ad67dbd5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.816588Z digest=sha256:37c425a43c24d1388f8b67d6fd4a73016daf8bab07ddc4671eccdb0324040a71

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.908655Z digest=sha256:0ef041430b021ba21c4a208dd5f181bf2d71ca41aca566034d120c3978ab1e84

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:17.984701Z digest=sha256:76e24b03d80ce23ddd91889dc1dd6aaefd4d6ee8b58f46b7a5499885dd353900

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.057328Z digest=sha256:06e4a7e23650ad412152c8d95e11e5ebe309890c8fe0daa3362cfaf204ddaf05

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.127266Z digest=sha256:e0e339417fbcfda8179a17b51b7e834b81f6646edd54be632994d2f772e551e1

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.191574Z digest=sha256:2c2b64311c60a960bcf591787985bcc9306856024cde73651a82c35d35ef16ff

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.274392Z digest=sha256:f53b2056a9614d7f3aa24c70eeba04146d33937ba0cd53d577119ea5fc5c74f1

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.358936Z digest=sha256:3f20e3c7ee0acae0bcaef29f319703cfad90d9d8e7b1e951310c94967d674d73

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.447619Z digest=sha256:b6828e96ec769b0934d6fc7c3e0132899d32410dea5044cff0ff1cb3409d2dbf

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

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:14:21.196000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.527978Z digest=sha256:befb3e875a3825093c7e30127569506a74ab86669920bd6d9395a69c6c5201e2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.617069Z digest=sha256:0595003d2696bf691bf8c9c6add98f26fc2f40f5834a9a3e008895882703a275

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.720292Z digest=sha256:81864b8481b00ce267c392c24b2808fcb94864eb55435d99c7eba0b6a445c77f

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

Resolution
verified exact
doi, observed 2026-08-07T13:14:19.414659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.792728Z digest=sha256:797167144c454257ba60fee7e9343597ede71a5255f25856bcc518e7a9fd413f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.863575Z digest=sha256:bcff3b08a0932582f1519548405cc0559e06f852a9d76f262ad2e431451ae06f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:18.943378Z digest=sha256:16131311ac1435aba2b52168fd1189a750e45cbc0e8addd929cf8c8d6c042bc2

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.

source=pdf_text observed=2026-08-07T13:14:19.004283Z digest=sha256:47f4cc7d75ce20071f87e1105559cede3acc8b02b858ceb34d6ad4bffb68d284

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:19.062592Z digest=sha256:901da7fea6012f69d15f3377291907acaae2391c90942ffab3ac52e0d2b868da

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:19.130096Z digest=sha256:656bd80cad904b54cc512e5b6e0e1021bc7d6fb1d70a4c96e81b492ed75b3b30

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:19.193468Z digest=sha256:1044da25a11e42557ff658d2bafc0e381e93408ec7354619d913a55d56f2a51b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T13:14:19.262570Z digest=sha256:d8bc8ee74bb4899d6742e3b445a4aab6c65f1a3eecc791d747610c1264b0e6e2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T06:02:40.158866Z digest=sha256:d2ed21bcb38a51229e3c2214c4bc0ba9a005bd3fe51d78715538b342e9983aad