Paper Citation Record · LEDGER

Robustness and Regularization in Hierarchical Re-Basin

As of 11 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2510.09174.

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

pith.paper-citation-record.v1
2510.09174 v3

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-21T20:34:15.461619Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

16 of 16 outbound references displayed

verified exact1
verified fuzzy14
unresolved0
parse uncertain1
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba9bf4c6-fd2b-4c1b-acda-4eb9787e46b0 · outbound

This paper cites Linear mode connectivity and the lottery ticket hypothesis.

Robustness and Regularization in Hierarchical Re-Basin Linear mode connectivity and the lottery ticket hypothesis

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.936355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1ea4cc8b-ba44-49bc-aa6d-433b8c18a4c7 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Robustness and Regularization in Hierarchical Re-Basin The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.948421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 75fd1585-c4c6-4ef2-8306-cd36a3549e6e · outbound

This paper cites Linear mode connectivity in multitask and continual learning.

Robustness and Regularization in Hierarchical Re-Basin Linear mode connectivity in multitask and continual learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.933634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 551a1d87-ca75-4e99-b823-f552c70bc379 · outbound

This paper cites Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks.

Robustness and Regularization in Hierarchical Re-Basin Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:34:20.861641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 85ad2463-6fd9-4695-b9f9-2cfc8fd534c3 · outbound

This paper cites Ainsworth et al.

Robustness and Regularization in Hierarchical Re-Basin Ainsworth et al

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.918642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2ec6ebc0-18d2-4d57-be34-6063ba57285f · outbound

This paper cites an unresolved cited work.

Robustness and Regularization in Hierarchical Re-Basin Unresolved cited work

Reference 6

Resolution: parse uncertain; raw_fallback, observed 2026-05-21T20:34:20.943436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d9c4e605-a841-4fdb-ab9c-971f5099b933 · outbound

This paper cites The role of permutation invariance in linear mode connectivity of neural networks.

Robustness and Regularization in Hierarchical Re-Basin The role of permutation invariance in linear mode connectivity of neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.928141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2baf6959-c737-4322-83be-f449706a7fc0 · outbound

This paper cites Exploring mode connectivity for pre-trained language models.

Robustness and Regularization in Hierarchical Re-Basin Exploring mode connectivity for pre-trained language models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.915463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d6fcb61f-cd4f-4fe6-a840-c5492a423142 · outbound

This paper cites Going beyond linear mode connectivity: The layerwise linear feature connectivity.

Robustness and Regularization in Hierarchical Re-Basin Going beyond linear mode connectivity: The layerwise linear feature connectivity

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.941248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a5b5d04d-14ba-4546-afbf-ab53f3172609 · outbound

This paper cites Federated learning with matched averaging.

Robustness and Regularization in Hierarchical Re-Basin Federated learning with matched averaging

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.946093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6476a499-102e-48d7-a133-31136030abbe · outbound

This paper cites Property inference attacks on fully connected neural networks us- ing permutation invariant representations.

Robustness and Regularization in Hierarchical Re-Basin Property inference attacks on fully connected neural networks us- ing permutation invariant representations

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.931782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 07ee5d18-1d01-491f-930b-6f3c79af2074 · outbound

This paper cites Deepfool: A simple and accurate method to fool deep neural networks.

Robustness and Regularization in Hierarchical Re-Basin Deepfool: A simple and accurate method to fool deep neural networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.938701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3a88e15b-3dab-46ec-8391-33275c0b37b5 · outbound

This paper cites Huang et al.

Robustness and Regularization in Hierarchical Re-Basin Huang et al

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.929790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cef55a88-0195-4c05-9c0c-63eb602ef9c9 · outbound

This paper cites The effects of adding noise during backpropagation training on a general- ization performance.Neural Computation, 8(3):643–674.

Robustness and Regularization in Hierarchical Re-Basin The effects of adding noise during backpropagation training on a general- ization performance.Neural Computation, 8(3):643–674

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.935851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9e6d4f57-ef84-4714-bf47-599ff5586263 · outbound

This paper cites Feature selection, l1 vs.

Robustness and Regularization in Hierarchical Re-Basin Feature selection, l1 vs

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.933784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c914a927-780d-4f82-a96e-fac27c484bff · outbound

This paper cites Analytical bounds on the local lipschitz constants of relu networks.IEEE Transactions on Neural Networks and Learning Systems.

Robustness and Regularization in Hierarchical Re-Basin Analytical bounds on the local lipschitz constants of relu networks.IEEE Transactions on Neural Networks and Learning Systems

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T20:34:20.921528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.