Paper Citation Record · LEDGER

CGD: Modifying the Loss Landscape by Gradient Regularization

As of 21 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2504.16182.

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

pith.paper-citation-record.v1
2504.16182 v3

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:24.992698Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

23 of 23 outbound references displayed

verified exact0
verified fuzzy7
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98b1bf19-32b7-4d81-bbfd-a24df0b006b0 · outbound

This paper cites Implicit Gradient Regularization.

CGD: Modifying the Loss Landscape by Gradient Regularization Implicit Gradient Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.914556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 713c6c98-37cf-43d4-8dcc-2fd3930904f1 · outbound

This paper cites Society for Industrial and Applied Mathematics (2014).

CGD: Modifying the Loss Landscape by Gradient Regularization Society for Industrial and Applied Mathematics (2014)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.919127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddec32a4-9b43-46d3-b77b-e4436931aed3 · outbound

This paper cites Mathematics of Computation21(99), 368–381 (1967).

CGD: Modifying the Loss Landscape by Gradient Regularization Mathematics of Computation21(99), 368–381 (1967)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.258991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d282e498-2dc4-4209-989c-65c2543b3c2d · outbound

This paper cites Journal of Statistical Mechanics: Theory and Experiment2019(12), 124018 (2019).

CGD: Modifying the Loss Landscape by Gradient Regularization Journal of Statistical Mechanics: Theory and Experiment2019(12), 124018 (2019)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.926784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf7094d8-ab71-4f6a-b42e-ffb0c85737a7 · outbound

This paper cites In: Advances in Neural Information Processing Systems.

CGD: Modifying the Loss Landscape by Gradient Regularization In: Advances in Neural Information Processing Systems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.249770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation edace42f-2d9d-484d-940a-9c064442aabb · outbound

This paper cites The Computer Journal 13(3), 317–322 (1970).

CGD: Modifying the Loss Landscape by Gradient Regularization The Computer Journal 13(3), 317–322 (1970)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.933960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48fd8485-79e5-4e47-bb4d-07e2e287b28b · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

CGD: Modifying the Loss Landscape by Gradient Regularization Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.937793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1c1e716-b973-41d3-a692-179638c95d34 · outbound

This paper cites Neural Computation 9(1), 1–42 (1997).

CGD: Modifying the Loss Landscape by Gradient Regularization Neural Computation 9(1), 1–42 (1997)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.941976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb3cff7a-089e-4a77-bf9c-dafd84b6738f · outbound

This paper cites In: Proceedings of the 40th International Conference on Machine Learning.

CGD: Modifying the Loss Landscape by Gradient Regularization In: Proceedings of the 40th International Conference on Machine Learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.238778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1cfabf72-ba6e-4683-8993-49a4217179b9 · outbound

This paper cites In: Machine Learning and Knowledge Discovery in Databases.

CGD: Modifying the Loss Landscape by Gradient Regularization In: Machine Learning and Knowledge Discovery in Databases

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.227693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 04c42943-ac7c-4def-b65c-57dccc90e514 · outbound

This paper cites On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima.

CGD: Modifying the Loss Landscape by Gradient Regularization On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.951973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3accb230-8ed8-41f3-998b-03c127043a08 · outbound

This paper cites In: Advances in Neural Information Process- ing Systems (2018), https://proceedings.neurips.cc/paper_files/paper/2018/file/ a41b3bb3e6b050b6c9067c67f663b915-Paper.pdf.

CGD: Modifying the Loss Landscape by Gradient Regularization In: Advances in Neural Information Process- ing Systems (2018), https://proceedings.neurips.cc/paper_files/paper/2018/file/ a41b3bb3e6b050b6c9067c67f663b915-Paper.pdf

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.217503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 995571ee-5bac-4cdb-b624-1762d192d324 · outbound

This paper cites Springer New York, 2nd edn.

CGD: Modifying the Loss Landscape by Gradient Regularization Springer New York, 2nd edn

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.958826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a8860cd-adfc-4a11-bb98-4cccdd0c3053 · outbound

This paper cites Neural Computation 6(1), 147–160 (1994).

CGD: Modifying the Loss Landscape by Gradient Regularization Neural Computation 6(1), 147–160 (1994)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.961738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d74a50d1-e8de-4354-9e58-60d902016127 · outbound

This paper cites USSR Com- putational Mathematics and Mathematical Physics 3(4), 864–878 (1963).

CGD: Modifying the Loss Landscape by Gradient Regularization USSR Com- putational Mathematics and Mathematical Physics 3(4), 864–878 (1963)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.964674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8499ced3-ed8b-441b-a52d-3f0d1e21f406 · outbound

This paper cites J., P., Bodas, T.: Practical first-order bayesian optimization algorithms.

CGD: Modifying the Loss Landscape by Gradient Regularization J., P., Bodas, T.: Practical first-order bayesian optimization algorithms

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.967808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 487a73bf-cb57-495c-982c-b3997eeb1fe2 · outbound

This paper cites An overview of gradient descent optimization algorithms.

CGD: Modifying the Loss Landscape by Gradient Regularization An overview of gradient descent optimization algorithms

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.970863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c5b8dbe-c619-4eba-8dff-92e9f9d284ab · outbound

This paper cites In: Proceedings of the 32nd International Conference on Machine Learning.

CGD: Modifying the Loss Landscape by Gradient Regularization In: Proceedings of the 32nd International Conference on Machine Learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.206520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7b7fe061-c67d-4684-8ae9-bb01e2d42015 · outbound

This paper cites On the Origin of Implicit Regularization in Stochastic Gradient Descent.

CGD: Modifying the Loss Landscape by Gradient Regularization On the Origin of Implicit Regularization in Stochastic Gradient Descent

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.977858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4a6b2d-e617-4ecb-a703-4d583462aefc · outbound

This paper cites an unresolved cited work.

CGD: Modifying the Loss Landscape by Gradient Regularization Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:17:25.196115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 92349c7c-af59-4e24-b645-319122dc7f06 · outbound

This paper cites Machine Learning8(3–4), 229–256 (1992).

CGD: Modifying the Loss Landscape by Gradient Regularization Machine Learning8(3–4), 229–256 (1992)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.985137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abdc6106-1b41-4eeb-b63d-b998c060c587 · outbound

This paper cites In: Proceedings of the 39th International Confer- ence on Machine Learning.

CGD: Modifying the Loss Landscape by Gradient Regularization In: Proceedings of the 39th International Confer- ence on Machine Learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:17:25.186560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 286444d5-a752-489c-9556-1abe146efc78 · outbound

This paper cites Surrogate Gap Minimization Improves Sharpness-Aware Training.

CGD: Modifying the Loss Landscape by Gradient Regularization Surrogate Gap Minimization Improves Sharpness-Aware Training

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.992698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.