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Paper Citation Record · LEDGER

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2210.11466.

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

pith.paper-citation-record.v1
2210.11466 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:13.508685Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-25T05:00:21.035915Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f62cf2ff-7cbf-49f0-97ca-0d85bccdeaca · inbound

Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning cites this paper.

Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:54:52.893045Z

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=2026-05-22T13:54:38.393967Z digest=sha256:894e0f945e16cb3112d23ae3788ee6a52cfd3c3fc4e066eb168168d4d4ef41c7

Observation 7424c8fc-b454-4235-843c-f4c8b92703db · inbound

FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts cites this paper.

FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:13.508685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:13.508685Z digest=sha256:4a175268effef3e978d0c854d5c40f2616cfa0122926abbddedf11da139a33ee

Observation 94f5a1e6-0573-4b0f-a634-62957dcbd085 · inbound

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning cites this paper.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T10:46:22.398872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:46:22.398872Z digest=sha256:5c6ad81f26983ac53446603e43bc02f08f83b532a83b525741f7ed18bf3f779c

Observation 5ed0e493-5f71-4aac-b93b-cf4bf6e729f8 · inbound

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices cites this paper.

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T05:44:11.207780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:44:11.207780Z digest=sha256:cc647c420ad9418fe2311dfea70d5b944c075c6eefa3bcc7ba5fb355fd278592

Observation a29d2beb-35de-4a15-a804-3ae4ca5a41fd · inbound

Feed Two Birds with One Scone: Exploiting Function-Space Regularization for Both OOD Robustness and ID Fine-Tuning Performance cites this paper.

Feed Two Birds with One Scone: Exploiting Function-Space Regularization for Both OOD Robustness and ID Fine-Tuning Performance Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T13:18:55.450431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:18:55.450431Z digest=sha256:87fadeaa591b618fa8f5274ebb4054573f4e1679ac9595cb65b33301f8c96687

Observation 8a79fb37-b36e-4af1-b08e-302f045b814f · inbound

Generalizable Deepfake Detection Based on Forgery-aware Layer Masking and Multi-artifact Subspace Decomposition cites this paper.

Generalizable Deepfake Detection Based on Forgery-aware Layer Masking and Multi-artifact Subspace Decomposition Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-16T18:33:15.277179Z

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=2026-05-16T18:32:04.723901Z digest=sha256:6a7ed38767767563f5796aceb937bfacaa7bf260b460adcfa96d72d540101476

Observation d2dab4e7-9a23-4939-ac70-f73c911105d7 · inbound

Intermediate Representations are Strong AI-Generated Image Detectors cites this paper.

Intermediate Representations are Strong AI-Generated Image Detectors Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:56:06.726897Z

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=2026-05-08T16:55:44.000342Z digest=sha256:fcc1e2cf59639f9862f17e044c6b557eda7a131c671dcf3986d650a8cb7b70b2

Observation 21b6eaf4-74c9-4295-a2dc-f5dcd713a503 · inbound

Selective, Regularized, and Calibrated: Harnessing Vision Foundation Models for Cross-Domain Few-Shot Semantic Segmentation cites this paper.

Selective, Regularized, and Calibrated: Harnessing Vision Foundation Models for Cross-Domain Few-Shot Semantic Segmentation Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:48:05.821084Z

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=2026-05-20T06:45:35.591459Z digest=sha256:354bc7cd4632e45c014e28ff11c6a8bb7ac74cd04267bf7e46ffad0ac534b47e

Observation e9c90708-46a8-4b4e-98f3-be7ff95dd28d · inbound

Sample-wise Targeted Adversarial Attacks on Test-time Adaptation cites this paper.

Sample-wise Targeted Adversarial Attacks on Test-time Adaptation Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:00:21.039549Z

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=2026-05-25T05:00:04.150887Z digest=sha256:0596bc8fee4e4935e7ce62b3e389c5f11318c3ab2e51a6bcb807368b0ac402ef

Observation 0e4b0a8e-2a7b-40ca-95f0-5f987e5f019b · inbound

Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry cites this paper.

Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-01T09:29:11.760996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T09:29:11.760996Z digest=sha256:f39bc0b5198f046473f2f268ab4f99429d899a0ba361c816566dcc56c256a905

Observation 584f640b-beda-4afc-9e1d-7dc1b69eab76 · inbound

SAFE-Merge: Data-Free Continual Model Merging with General Knowledge Preservation cites this paper.

SAFE-Merge: Data-Free Continual Model Merging with General Knowledge Preservation Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T00:32:21.354771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:32:21.354771Z digest=sha256:b4150d017825ae783f7737052d465115622887a791de61129d9a15f05e31354f