Paper Citation Record · LEDGER

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks

As of 18 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2504.17618.

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

pith.paper-citation-record.v1
2504.17618 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:39:10.899279Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

21 of 21 outbound references displayed

verified exact2
verified fuzzy1
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d1799c44-ceac-4916-8e81-7b6ed819523d · outbound

This paper cites Visualizing the Loss Landscape of Neural Nets.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Visualizing the Loss Landscape of Neural Nets

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.803606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c6ad515-2eeb-4434-a899-75aec83ec2f3 · outbound

This paper cites An empirical analysis of the optimization of deep network loss surfaces.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks An empirical analysis of the optimization of deep network loss surfaces

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.809236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb30592a-32f6-4da7-b356-ec0924597b71 · outbound

This paper cites Emergent properties of the local geometry of neural loss landscapes.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Emergent properties of the local geometry of neural loss landscapes

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.814142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9ca2d1e-5e70-43f7-980c-1d8886a01fcb · outbound

This paper cites PyHessian: Neural Networks Through the Lens of the Hessian.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks PyHessian: Neural Networks Through the Lens of the Hessian

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.818866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6bb62bb-6b69-4d38-b155-c8d8e84df9ce · outbound

This paper cites Investigating generalization capabilities of neural networks by means of loss landscapes and Hessian analysis.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Investigating generalization capabilities of neural networks by means of loss landscapes and Hessian analysis

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:39:11.112399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6f756200-ea20-42c0-bc9e-be06c4023aeb · outbound

This paper cites Deep residual learning for image recognition,.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Deep residual learning for image recognition,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.829517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e26dc51-3a2c-4a84-87fd-41ff5dbce8c5 · outbound

This paper cites Why Transformers Need Adam: A Hessian Perspective.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Why Transformers Need Adam: A Hessian Perspective

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.838589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 661410b8-0ff9-448c-89aa-5f50dda374f2 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.844065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 596b2999-6017-4b7d-8bad-3ae5b8a74138 · outbound

This paper cites Improving language understanding by generative pre- training,.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Improving language understanding by generative pre- training,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:39:11.204220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81c6b8b6-1d4b-4356-9a93-145d71df8ff2 · outbound

This paper cites How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.853175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aaa1803-7f04-4d16-83fe-217b7e9dc6fe · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Imagenet: A large-scale hierarchical image database,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.857690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60f0fb90-787a-408b-bab8-f402d8b205f5 · outbound

This paper cites Do ImageNet Classifiers Generalize to ImageNet?.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Do ImageNet Classifiers Generalize to ImageNet?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.862358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ac045ce-6cd1-4edd-86bd-fc889c72aba3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Adam: A Method for Stochastic Optimization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.867400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70df41f0-634c-4b24-943f-eb35c9ed958e · outbound

This paper cites An overview of gradient descent optimization algorithms.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks An overview of gradient descent optimization algorithms

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.872037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed927e3d-e702-4752-83db-d02c5c2e0856 · outbound

This paper cites CINIC-10 is not ImageNet or CIFAR-10.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks CINIC-10 is not ImageNet or CIFAR-10

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.876932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8baad6bb-bbfd-4eaa-8cda-e75fb75ba72e · outbound

This paper cites Decoupled Weight Decay Regularization.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Decoupled Weight Decay Regularization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.881551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 907c005f-ce32-4c64-a4a4-b49560e102ce · outbound

This paper cites Learning multiple layers of features from tiny images,.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Learning multiple layers of features from tiny images,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.885698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e62cff3d-2cc4-4ad6-8a47-e5e179b2a953 · outbound

This paper cites RandAugment: Practical automated data augmentation with a reduced search space.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks RandAugment: Practical automated data augmentation with a reduced search space

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.890005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b340db0c-b9ef-4b53-83af-9c1a2bef714c · outbound

This paper cites ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:39:10.952652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 483e5bd4-7141-4d8b-ac4b-cd068e94b9cf · outbound

This paper cites Visualizing high-dimensional loss landscapes with hessian directions,.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Visualizing high-dimensional loss landscapes with hessian directions,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.899279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7de2a842-f3a1-4aac-bf17-5d1023bf686b · outbound

This paper cites Deep Residual Learning for Image Recognition.

The effects of Hessian eigenvalue spectral density type on the applicability of Hessian analysis to generalization capability assessment of neural networks Deep Residual Learning for Image Recognition

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-16T10:39:10.833778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.