Paper Citation Record · LEDGER

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy

As of 7 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2507.13260.

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

pith.paper-citation-record.v1
2507.13260 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:35:28.623883Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T06:35:33.560079Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T06:36:36.481883Z

Reference resolution

34 of 34 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d91d60c-52ed-4658-8aa7-3ca940d19728 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Qlora: Efficient finetuning of quantized llms

Reference 1

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Observation 8f9d5aea-9e0f-4a57-9829-106aa580b1ca · outbound

This paper cites Effi- cient adaptation of large vision transformer via adapter re- composing.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Effi- cient adaptation of large vision transformer via adapter re- composing

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:34.064907Z

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Observation 2b012507-0481-45f8-9f79-7f26c51fc305 · outbound

This paper cites Low-rank rescaled vision transformer fine-tuning: A residual design approach.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Low-rank rescaled vision transformer fine-tuning: A residual design approach

Reference 3

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Observation 5874c01c-a598-42cf-805e-43f62c7afb5a · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy An image is worth 16x16 words: Trans- formers for image recognition at scale

Reference 4

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Observation b6fd01b0-acb1-4dcf-9c6c-838d80891073 · outbound

This paper cites Fine-grained car detection for vi- sual census estimation.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Fine-grained car detection for vi- sual census estimation

Reference 5

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Observation c947a22c-0e7b-46c1-8805-84892b222a70 · outbound

This paper cites Foundations of ma- chine learning.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Foundations of ma- chine learning

Reference 6

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Observation eaa88237-1eb9-4f91-b01f-e0adebecca88 · outbound

This paper cites Neural network methods in natural lan- guage processing.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Neural network methods in natural lan- guage processing

Reference 7

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Observation 2c08c26a-d372-4ba3-865e-73cef7ef3a7d · outbound

This paper cites Matrix computa- tions.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Matrix computa- tions

Reference 8

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Observation 8601a7ef-f7b0-4e8d-904c-9e2482833dea · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Parameter-efficient transfer learning for nlp

Reference 9

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Observation f84d05d5-b99f-4c44-bd06-929b8ba69aed · outbound

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

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Lora: Low- rank adaptation of large language models

Reference 10

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Observation 5b1960b4-7c9e-40dc-b4d7-0b69238258b1 · outbound

This paper cites Vi- sual prompt tuning.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Vi- sual prompt tuning

Reference 11

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Observation a2371568-9cdf-47ac-a7a6-85e723a26d70 · outbound

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

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Fact: Factor-tuning for lightweight adaptation on vision transformer

Reference 12

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Observation a3753700-fbc5-47cc-93d3-f35627237510 · outbound

This paper cites Novel dataset for fine-grained image categorization: Stanford dogs.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Novel dataset for fine-grained image categorization: Stanford dogs

Reference 13

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Observation 98cf35f7-e1d3-4a04-b39b-abc6fb6ab7d7 · outbound

This paper cites VeRA: Vector-based Random Matrix Adaptation.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy VeRA: Vector-based Random Matrix Adaptation

Reference 14

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Observation f77cea2a-19e2-444b-a0c6-441b7ef27e30 · outbound

This paper cites Scaling & shifting your features: A new baseline for efficient model tuning.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Scaling & shifting your features: A new baseline for efficient model tuning

Reference 15

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Observation a4d1d1ed-4f4b-4df9-88d3-dc1409a3ea95 · outbound

This paper cites Dora: Weight-decomposed low-rank adaptation.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Dora: Weight-decomposed low-rank adaptation

Reference 16

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Observation 3e4ddd15-4f06-4a67-9928-31cf98546bf8 · outbound

This paper cites Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization

Reference 17

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Observation b9b16e9f-e4df-49dc-9cdc-c0f7a906a015 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Swin transformer: Hierarchical vision transformer using shifted windows

Reference 18

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Observation 7d98a441-1af6-49ef-b081-4d3af6ad9d5a · outbound

This paper cites Towards Efficient Visual Adaption via Structural Re-parameterization.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Towards Efficient Visual Adaption via Structural Re-parameterization

Reference 19

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Observation ce2737c7-5dd7-40fe-ab9e-49ed474e58e4 · outbound

This paper cites Moil: Momentum imita- tion learning for efficient vision-language adaptation.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Moil: Momentum imita- tion learning for efficient vision-language adaptation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:31.013111Z

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Observation 92a729b3-67b1-4f74-9b30-83e1bb57713f · outbound

This paper cites Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation

Reference 21

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Observation ee20198a-4ab1-4882-921a-ec99cf938f66 · outbound

This paper cites Simple theorems, proofs, and derivations in quantum chemistry.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Simple theorems, proofs, and derivations in quantum chemistry

Reference 22

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Observation 4215e3f7-5ad9-4e6a-9e41-3caf4a987357 · outbound

This paper cites Automated flower classification over a large number of classes.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Automated flower classification over a large number of classes

Reference 23

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Observation 11b68d92-a58b-4bf0-a9b7-7ca603d94899 · outbound

This paper cites Controlling text-to-image diffusion by orthogo- nal finetuning.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Controlling text-to-image diffusion by orthogo- nal finetuning

Reference 24

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Observation e629943e-cfd6-4168-80ff-9e5106e7eed3 · outbound

This paper cites Deep learning in neural networks: An overview.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Deep learning in neural networks: An overview

Reference 25

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Observation 12f4a9a0-b6c6-4638-98a6-6f2cf86e5149 · outbound

This paper cites An adaptive strategy selection method with reinforcement learning for robotic soccer games.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy An adaptive strategy selection method with reinforcement learning for robotic soccer games

Reference 26

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This paper cites Adapters strike back.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Adapters strike back

Reference 27

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Observation 243b9b7d-daf8-44e9-bd1f-d2ec792bc3f9 · outbound

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Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Numerical linear alge- bra

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:35:29.577417Z

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Observation 6a6e7502-5695-4e9c-b949-b9fc71c5394c · outbound

This paper cites Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection

Reference 29

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This paper cites Deep neural networks for im- age classification.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Deep neural networks for im- age classification

Reference 30

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Observation 8094ca3d-6d93-45f7-87a9-46e07f64b450 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy The caltech-ucsd birds-200-2011 dataset

Reference 31

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

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 32

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This paper cites A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark.

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark

Reference 33

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Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy The visual task adaptation benchmark

Reference 34

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Pith citing papers

Observation ad96f94c-b7f0-4d7b-96d7-47a488a454e5 · inbound

Understanding and Enforcing Weight Disentanglement in Task Arithmetic cites this paper.

Understanding and Enforcing Weight Disentanglement in Task Arithmetic Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy

Reference 49

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Source-reported events for the cited work

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