Paper Citation Record · LEDGER

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification

As of 13 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2508.07577.

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

pith.paper-citation-record.v1
2508.07577 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:05:31.290393Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

34 of 34 outbound references displayed

verified exact0
verified fuzzy20
unresolved14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c74dd93-e130-4ebe-b0ca-78c1bdc7a65e · outbound

This paper cites Bach: Grand challenge on breast cancer histology images.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Bach: Grand challenge on breast cancer histology images

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.887113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7616a902-e169-482f-ae9a-d23304f7476c · outbound

This paper cites Layer Normalization.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Layer Normalization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.128000Z

Source-reported events for the cited work

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Observation 15b8d6e9-dd26-4372-8d86-b14c3ffa1a90 · outbound

This paper cites o l \"o nen, Satu Mustjoki, and Oscar Br \.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification o l \"o nen, Satu Mustjoki, and Oscar Br \

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.873858Z

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Observation e4c5f54b-065b-4e55-90b1-ae750dadce33 · outbound

This paper cites Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.136572Z

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Observation 69493c59-1b2d-4ec7-9187-5cdd4492a7ba · outbound

This paper cites Describing textures in the wild.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Describing textures in the wild

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.860721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 63d40631-1fae-44ea-bed9-022f1b4dd95f · outbound

This paper cites On the effectiveness of layernorm tuning for continual learning in vision transformers.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification On the effectiveness of layernorm tuning for continual learning in vision transformers

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.848025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d32f711-a32a-4423-bcce-0ba9e64fb91a · outbound

This paper cites Multimodal Whole Slide Foundation Model for Pathology.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Multimodal Whole Slide Foundation Model for Pathology

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.149976Z

Source-reported events for the cited work

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Observation 5a8b87b3-2ff3-4566-ab95-77a51305e432 · outbound

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

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.153968Z

Source-reported events for the cited work

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Observation 9827b0a1-f2b3-42db-9e3d-f05150c08d35 · outbound

This paper cites The Expressive Power of Tuning Only the Normalization Layers.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification The Expressive Power of Tuning Only the Normalization Layers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.158369Z

Source-reported events for the cited work

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Observation fe016dda-342f-4070-9e42-c6540be33f65 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Masked autoencoders are scalable vision learners

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.835445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6c16f01d-bdc3-4a66-8034-a9be1fe347ac · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Parameter-efficient transfer learning for nlp

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.823179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 33de2fcf-ef51-4860-8069-ef56b08d9d03 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Lora: Low-rank adaptation of large language models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.810130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation aec3d6c7-b3f9-40d3-9b66-403e109760dc · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.796675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1375129a-18d1-434f-a447-65b610887029 · outbound

This paper cites Visual prompt tuning.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Visual prompt tuning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.783169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4b0dfa3b-93a7-476e-8bdd-404793ac5e9f · outbound

This paper cites Fact: Factor-tuning for lightweight adaptation on vision transformer.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Fact: Factor-tuning for lightweight adaptation on vision transformer

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.769361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 605a62a3-209e-433a-b524-86864bf21fe3 · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.184727Z

Source-reported events for the cited work

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Observation fb4191d4-ca7b-47dc-9c62-5eeeac0d98ea · outbound

This paper cites A visual-language foundation model for computational pathology.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification A visual-language foundation model for computational pathology

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.756594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 274fe8c1-49e8-463c-bbe5-9ca0fdb0aa3f · outbound

This paper cites an unresolved cited work.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-05T22:05:31.743995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dad2e229-01c5-45c6-9023-039e5ad26404 · outbound

This paper cites Scalable diffusion models with transformers.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Scalable diffusion models with transformers

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.731366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b0b3b486-1f09-4fa2-8166-bad2891acb88 · outbound

This paper cites Moment matching for multi-source domain adaptation.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Moment matching for multi-source domain adaptation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.718245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 43b117eb-dd29-46f6-a6b6-5475cf2dbe5b · outbound

This paper cites Parameter-Efficient Tuning on Layer Normalization for Pre-trained Language Models.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Parameter-Efficient Tuning on Layer Normalization for Pre-trained Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.203945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e952d51c-bb49-40af-aefa-abfe5dbbd581 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Learning transferable visual models from natural language supervision

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.208301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52f69b16-5f31-4406-95e6-2654b1937f22 · outbound

This paper cites Parameter-efficient multi-task and transfer learning, June 13 2023.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Parameter-efficient multi-task and transfer learning, June 13 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.696026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b5f0f03c-af8b-4907-a87d-24aacc1860e8 · outbound

This paper cites Gland segmentation in colon histology images: The glas challenge contest.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Gland segmentation in colon histology images: The glas challenge contest

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.682957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fbbdaa63-9513-44e2-8442-dd4f300f9e77 · outbound

This paper cites A dataset for breast cancer histopathological image classification.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification A dataset for breast cancer histopathological image classification

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.668448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 38f0c0ac-22cd-42d8-82f5-3b292bdfd5d4 · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.239572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a54b057a-98b8-406f-86e2-d94f508c6a6e · outbound

This paper cites LayerNorm: A key component in parameter-efficient fine-tuning.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification LayerNorm: A key component in parameter-efficient fine-tuning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.257892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cd4b978-5161-4386-ac14-d02c9da4c8a4 · outbound

This paper cites A pathology foundation model for cancer diagnosis and prognosis prediction.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification A pathology foundation model for cancer diagnosis and prognosis prediction

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.655272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cb39e61c-2090-4100-b6d6-53f82c1ff25b · outbound

This paper cites Group normalization.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Group normalization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.641864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1b9ed040-d721-423e-9a54-49bdde28b415 · outbound

This paper cites Sun database: Large-scale scene recognition from abbey to zoo.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Sun database: Large-scale scene recognition from abbey to zoo

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.629472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fdf39c2a-7418-44c7-9bea-fd17158fe6e1 · outbound

This paper cites Understanding and improving layer normalization.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Understanding and improving layer normalization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:05:31.615737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 18a79a0f-428f-41ca-a542-6156ee9f0aaf · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.281257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae76d5cd-8e71-437a-abfa-5da13c3106dc · outbound

This paper cites Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.286262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acfd7169-d380-4f86-9d17-639b344d410c · outbound

This paper cites Transformers without Normalization.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Transformers without Normalization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:31.290393Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.