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Paper Citation Record · LEDGER

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation

As of 10 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2506.02453.

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

pith.paper-citation-record.v1
2506.02453 v2

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:29:55.274473Z

measured 75 of 75 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T10:47:38.553051Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:48:12.689751Z

Reference resolution

74 of 74 outbound references displayed

  • verified exact1
  • verified fuzzy34
  • unresolved38
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9b05fa73-53af-45b4-9402-ba764fa435a4 · outbound

This paper cites Progressive feature alignment for unsupervised domain adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Progressive feature alignment for unsupervised domain adaptation

Reference 1

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raw_fallback, observed 2026-08-07T11:29:56.804566Z

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.

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Observation 3755e638-3f61-4006-9725-a481430fe98a · outbound

This paper cites Harmonizing transfer- ability and discriminability for adapting object detectors.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Harmonizing transfer- ability and discriminability for adapting object detectors

Reference 2

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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.

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Observation be7c04e7-d21b-413e-b8b5-61dfd4128078 · outbound

This paper cites I3net: Implicit instance-invariant network for adapting one-stage object detectors.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation I3net: Implicit instance-invariant network for adapting one-stage object detectors

Reference 3

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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.

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Observation 1d3a8e1c-e5e0-4498-82fc-aee41a868c8a · outbound

This paper cites Contrastive test-time adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Contrastive test-time adaptation

Reference 4

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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=2026-08-07T11:29:51.069344Z digest=sha256:868ca8f432f15d9da16f1f887f560b87fd9fcb4c0f515ab2e106217bc86ee1ee

Observation 7dcae4c7-1fb6-488b-b0bb-0fa33629f191 · outbound

This paper cites Amplitude-phase recombination: Rethinking robustness of convolutional neural networks in frequency domain.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Amplitude-phase recombination: Rethinking robustness of convolutional neural networks in frequency domain

Reference 5

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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.

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Observation b41f8e46-c7a4-4e3a-affb-6014c6be0c92 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation The cityscapes dataset for semantic urban scene understanding

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d190577e-e4e7-41d6-8e0b-0557df7a6bba · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Imagenet: A large- scale hierarchical image database

Reference 7

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Observation e7339fca-6072-4e8e-b1cd-cc93500562d7 · outbound

This paper cites Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation

Reference 8

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source=pdf_text observed=2026-08-07T11:29:51.468838Z digest=sha256:865d158602b94fd52a298fcd7c66ee6e1fa7ddbf9a1b74b5d2972fcd40f98f07

Observation 6e1d20aa-eb68-4357-805e-8a3deb633f63 · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Efficient adaptation of large vision transformer via adapter re-composing

Reference 9

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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.

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Observation 53bcd586-de31-43bc-8f50-96c7fa4b9d1d · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

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Source-reported events for the cited work

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Observation 18b3bea3-29bf-49cc-83b9-f8225134a2f6 · outbound

This paper cites Test time adaptation through perturbation robustness.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Test time adaptation through perturbation robustness

Reference 11

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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.

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Observation 7cd42b24-eefc-4fa5-81b0-f8455f18a585 · outbound

This paper cites Decorate the newcomers: Visual domain prompt for continual test time adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Decorate the newcomers: Visual domain prompt for continual test time adaptation

Reference 12

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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.

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Observation 079492ed-794e-428f-b01d-45c85244e2f5 · outbound

This paper cites Visual Prompt Tuning for Test-time Domain Adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Visual Prompt Tuning for Test-time Domain Adaptation

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 117ca488-3449-4655-bf6f-0091873c668b · outbound

This paper cites Note: Robust continual test-time adaptation against temporal correlation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Note: Robust continual test-time adaptation against temporal correlation

Reference 14

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Unavailable: canonical work link unavailable.

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Observation 244fdfb2-2188-4b3a-8f92-d194e753d8d5 · outbound

This paper cites Sotta: Robust test-time adaptation on noisy data streams.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Sotta: Robust test-time adaptation on noisy data streams

Reference 15

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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.

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Observation 2e0320ca-d2cc-4ba8-9376-9e8346ca1dba · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 95915899-834b-4525-b84e-4cdbfa9dd2cc · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a402cd4c-a025-43ee-9866-c45cab180834 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Parameter-efficient transfer learning for nlp

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cec713fd-643d-417c-ad10-77a49a2f43c7 · outbound

This paper cites Unitary triangularization of a nonsymmetric matrix.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Unitary triangularization of a nonsymmetric matrix

Reference 19

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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.

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Observation b57180e6-ca0c-4494-bb7d-7abff170267a · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Lora: Low-rank adaptation of large language models

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8ace01e2-affb-42f9-9525-9d8f429cd38e · outbound

This paper cites Fsdr: Frequency space domain randomization for domain generalization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Fsdr: Frequency space domain randomization for domain generalization

Reference 21

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Unavailable: canonical work link unavailable.

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Observation 0adc7834-13a9-4c9d-bebb-931d68829880 · outbound

This paper cites Test-time classifier adjustment module for model-agnostic domain generalization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Test-time classifier adjustment module for model-agnostic domain generalization

Reference 22

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raw_fallback, observed 2026-08-07T11:29:56.541231Z

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.

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Observation ec5e9659-4f20-4785-afdc-e9419addc0e0 · outbound

This paper cites Test-Time Adaptation via Self-Training with Nearest Neighbor Information.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Test-Time Adaptation via Self-Training with Nearest Neighbor Information

Reference 23

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Observation c2aa7a9e-a284-4f79-ab49-f96f6729c295 · outbound

This paper cites Feature stylization and domain-aware contrastive learning for domain generalization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Feature stylization and domain-aware contrastive learning for domain generalization

Reference 24

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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.

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Observation e8ce5a2f-eea1-4741-9c49-242bb0c13765 · outbound

This paper cites Visual prompt tuning.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Visual prompt tuning

Reference 25

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Observation 4c573c19-a010-4b1a-bce7-25a25da78b48 · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Learning multiple layers of features from tiny images

Reference 26

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Observation 317ed056-65da-491a-96f8-071fe5d0d795 · outbound

This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks

Reference 27

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raw_fallback, observed 2026-08-07T11:29:56.468089Z

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.

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Observation 342b4f56-c7ad-4c58-9fb8-b78e18897ab5 · outbound

This paper cites Decompose, adjust, compose: Effective normalization by playing with frequency for domain generalization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Decompose, adjust, compose: Effective normalization by playing with frequency for domain generalization

Reference 28

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raw_fallback, observed 2026-08-07T11:29:56.449369Z

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.

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Observation 4abfed15-00f1-4d8f-ba38-3e022003fe55 · outbound

This paper cites A comprehensive survey on test-time adaptation under distribution shifts.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation A comprehensive survey on test-time adaptation under distribution shifts

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 000162c0-851b-4494-a79e-a6c7b38f6832 · outbound

This paper cites Deep frequency filtering for domain generalization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Deep frequency filtering for domain generalization

Reference 30

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raw_fallback, observed 2026-08-07T11:29:56.417807Z

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.

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Observation 6018fc39-251a-405d-a7cd-0c7bbfa4d8cb · outbound

This paper cites Continual-mae: Adaptive distribution masked autoencoders for continual test-time adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Continual-mae: Adaptive distribution masked autoencoders for continual test-time adaptation

Reference 31

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raw_fallback, observed 2026-08-07T11:29:56.397291Z

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.

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Observation 42d0acb8-94c6-4a4e-a000-6dc4cb2f6685 · outbound

This paper cites ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 78483a85-e6ab-4270-a9f7-dd8f6dbe357a · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Dora: Weight-decomposed low-rank adaptation

Reference 33

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Unavailable: canonical work link unavailable.

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Observation eb646c3a-68e8-427a-a68d-997bc48a1817 · outbound

This paper cites Learning towards minimum hyperspherical energy.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Learning towards minimum hyperspherical energy

Reference 34

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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.

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Observation dca624c6-bddc-4f42-b67c-959042048ba8 · outbound

This paper cites Orthogonal over-parameterized training.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Orthogonal over-parameterized training

Reference 35

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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.

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Observation 5a6b4914-f4bf-48b1-9df6-4812ffc08fa7 · outbound

This paper cites Decoupled networks.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Decoupled networks

Reference 36

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source=pdf_text observed=2026-08-07T11:29:53.848171Z digest=sha256:9d3de52cee32f7f16d80784618a68cf95db589c4e07355a0a826681f74f03a0c

Observation 5039927c-7bc9-460d-902b-b2768841f797 · outbound

This paper cites Deep hyperspherical learning.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Deep hyperspherical learning

Reference 37

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source=pdf_text observed=2026-08-07T11:29:54.035716Z digest=sha256:75e39dfd27516b968e6650b3b8576cadeaca37f8580bb731d57cdc5a2acba32c

Observation 98755455-38ed-4a0f-aeed-53974e20368a · outbound

This paper cites Decoupled Weight Decay Regularization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Decoupled Weight Decay Regularization

Reference 38

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source=pdf_text observed=2026-08-07T11:29:54.078416Z digest=sha256:f7c92e4c88ac04beaa0fecbb7cc951dcb3000253830663c81b668191835d1ac6

Observation fee0ad5f-8ca7-4b6f-8c70-fd260f8ab4c0 · outbound

This paper cites Universal test-time adaptation through weight ensembling, diversity weighting, and prior correction.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Universal test-time adaptation through weight ensembling, diversity weighting, and prior correction

Reference 39

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source=pdf_text observed=2026-08-07T11:29:54.085392Z digest=sha256:6d91f76e1a5aa6fa4d140beb367559a79fce954ec193af07606079e67690fafb

Observation 728448bc-d7a9-4997-83fa-8ad5920854ba · outbound

This paper cites Comparing vision transformers and convolutional neural networks for image classification: A literature review.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Comparing vision transformers and convolutional neural networks for image classification: A literature review

Reference 40

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source=pdf_text observed=2026-08-07T11:29:54.091563Z digest=sha256:e0c26a66ccee7e52a4dc94b55a8e6b1c117fd8d717e20bdeaf490375c9f1ab55

Observation a471cc4f-5a4c-423d-9335-ef1e3a4cef4c · outbound

This paper cites Image segmentation using deep learning: A survey.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Image segmentation using deep learning: A survey

Reference 41

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source=pdf_text observed=2026-08-07T11:29:54.117109Z digest=sha256:56b7470d5aad9ee1767268c326aa7057e2bbd615f0ce9640c5a730e74b203cfd

Observation 4188a1d4-1c2d-4ff6-8b3d-f6af32766124 · outbound

This paper cites Actmad: Activation matching to align distributions for test-time-training.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Actmad: Activation matching to align distributions for test-time-training

Reference 42

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:29:54.188550Z digest=sha256:62c02d275c272dd040469e290913c01eb637aef2b234f4055e69bf8a50b311a5

Observation e3cccf90-687e-4952-9edc-b3f6d1fdf9d1 · outbound

This paper cites Test-Time Model Adaptation with Only Forward Passes.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Test-Time Model Adaptation with Only Forward Passes

Reference 43

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source=pdf_text observed=2026-08-07T11:29:54.241398Z digest=sha256:fef76a0d02c04cc6984eb64b250796183a3fefeb3954e750da5e56c828d98058

Observation 2f3208fd-6b7f-4f10-8a31-818d7ec6e7c5 · outbound

This paper cites Efficient test-time model adaptation without forgetting.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Efficient test-time model adaptation without forgetting

Reference 44

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source=pdf_text observed=2026-08-07T11:29:54.320975Z digest=sha256:710bc39bbc1f45d7dcef444a0c5df5d40d6aaffbdf37c1cd88f415d3c9de7538

Observation 0375ca6c-5b37-44f2-aa80-64132e1ada13 · outbound

This paper cites Towards Stable Test-Time Adaptation in Dynamic Wild World.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Towards Stable Test-Time Adaptation in Dynamic Wild World

Reference 45

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source=pdf_text observed=2026-08-07T11:29:54.362600Z digest=sha256:537cf4eb714ef65e4f64330fbc5e07e698f6ec2919b4512df2a05a907dae7f4f

Observation b6b731d0-532e-4a98-8216-5cb6100ace6b · outbound

This paper cites The fast Fourier transform.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation The fast Fourier transform

Reference 46

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source=pdf_text observed=2026-08-07T11:29:54.456590Z digest=sha256:d98e13da51271cd80c031d821988e4dcd5bd6e2246dcc4ef137befe223589946

Observation 97d4131d-4ef8-4d82-b7d7-fac43c7b6fa4 · outbound

This paper cites Learning How to Ask: Querying LMs with Mixtures of Soft Prompts.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Learning How to Ask: Querying LMs with Mixtures of Soft Prompts

Reference 47

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source=pdf_text observed=2026-08-07T11:29:54.518680Z digest=sha256:f367535cd1b7d68f8f725e9f0c060dd84ae66556739e6ec2a9cb4cdcb284bea4

Observation 324a8b2a-f2b6-4a70-9429-6827305494eb · outbound

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

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Controlling text-to-image diffusion by orthogonal finetuning

Reference 48

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source=pdf_text observed=2026-08-07T11:29:54.591082Z digest=sha256:a5035395deab3c7ac7e2a076dda0aadec9bd527bbbe419e09db46c0faae4d784

Observation dc87c5ed-c727-4877-8fa3-d2f274a99c5a · outbound

This paper cites Do imagenet classifiers generalize to imagenet? In International conference on machine learning, pages 5389–5400.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Do imagenet classifiers generalize to imagenet? In International conference on machine learning, pages 5389–5400

Reference 49

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source=pdf_text observed=2026-08-07T11:29:54.596931Z digest=sha256:8d11a738d5d902168cfb10a06932494e9cd0864073b0e046ba3f62093dc9c28a

Observation d52fab38-56c5-4f04-a170-0fbbcce3e5b5 · outbound

This paper cites ImageNet-21K Pretraining for the Masses.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation ImageNet-21K Pretraining for the Masses

Reference 50

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source=pdf_text observed=2026-08-07T11:29:54.641798Z digest=sha256:36430a9e95ba73aff853ecac60b3f4cc7c2bb814ed49e5c7ac931ef18115d65a

Observation 0cd91477-817f-4573-a589-3bf8555ffb3d · outbound

This paper cites Acdc: The adverse conditions dataset with correspondences for semantic driving scene understanding.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Acdc: The adverse conditions dataset with correspondences for semantic driving scene understanding

Reference 51

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source=pdf_text observed=2026-08-07T11:29:54.712635Z digest=sha256:de073ec69bf0c1df8701a0e6085d9ccc783d715890c030e6b0bb30a7be0f4235

Observation 2df67777-16ed-4e7f-9ca3-e9931e7c9ecd · outbound

This paper cites Test-time prompt tuning for zero-shot generalization in vision-language models.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Test-time prompt tuning for zero-shot generalization in vision-language models

Reference 52

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source=pdf_text observed=2026-08-07T11:29:54.799357Z digest=sha256:0b1683df32941e63bccc415bf12e48553d3588dc9e712b8e4f0e833a0a695cef

Observation ca05b571-2cd3-49f6-87dd-460368a4a17a · outbound

This paper cites Ecotta: Memory-efficient continual test-time adaptation via self-distilled regularization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Ecotta: Memory-efficient continual test-time adaptation via self-distilled regularization

Reference 53

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source=pdf_text observed=2026-08-07T11:29:54.876831Z digest=sha256:b962f39a748b36667293ebbf7cc02db1e10347f4176fa2b830015e8ea6472721

Observation 5d589ac0-7f58-4670-811b-29a48f6327ff · outbound

This paper cites Hyperspherical consistency regularization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Hyperspherical consistency regularization

Reference 54

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source=pdf_text observed=2026-08-07T11:29:54.980637Z digest=sha256:227bdea83e4475fe0b0f251a0bfdb7ef616b5b61703ff6b65115d27030e8f23d

Observation 07e3647f-6067-4731-b332-aa6f5217c852 · outbound

This paper cites Tesla: Test- time self-learning with automatic adversarial augmentation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Tesla: Test- time self-learning with automatic adversarial augmentation

Reference 55

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source=pdf_text observed=2026-08-07T11:29:55.052430Z digest=sha256:5f952251fc37e129b8a9d15403527beb1611759b9d28b982eec025d8c6c23f49

Observation 3a07056e-5b30-4c9a-84c6-6678befbacc6 · outbound

This paper cites Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation

Reference 56

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source=pdf_text observed=2026-08-07T11:29:55.106301Z digest=sha256:878a4d6488f52f45d3b2e59a9e6eb568f9eddee4c0c4877eb25bddd8d85ce479

Observation 73f4db6f-c7c7-4930-a298-2befbedbde0e · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 57

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source=pdf_text observed=2026-08-07T11:29:55.129719Z digest=sha256:8699714c6b1c627ad7064581183a0ab5d541bd3e9661c5ef2096db02a40b3660

Observation 95fae75b-8016-4b88-9dc3-cf538bf2d350 · outbound

This paper cites Continual test-time domain adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Continual test-time domain adaptation

Reference 58

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source=pdf_text observed=2026-08-07T11:29:55.138691Z digest=sha256:5960ec097d8c0411bba25082be2d33cff7a7df0a7db03421295f14d9e968fd69

Observation c32f1464-6f9c-4562-92c5-fbf96686234a · outbound

This paper cites Feature alignment and uniformity for test time adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Feature alignment and uniformity for test time adaptation

Reference 59

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source=pdf_text observed=2026-08-07T11:29:55.149929Z digest=sha256:4fedbc8214384ab48a5462470895d75e86a1ef492c39d43bbcbda086208bf732

Observation 0a4580de-d874-4fbc-b39f-8f8f86b3c56f · outbound

This paper cites In search of lost online test-time adaptation: A survey.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation In search of lost online test-time adaptation: A survey

Reference 60

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source=pdf_text observed=2026-08-07T11:29:55.157917Z digest=sha256:066b9354aa6c1d1d488637aed393adcd563cf43553f74d23b894a0460ea3747c

Observation 994d3f1c-8f83-424d-9f25-bddce71ee93d · outbound

This paper cites Beyond Model Adaptation at Test Time: A Survey.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Beyond Model Adaptation at Test Time: A Survey

Reference 61

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source=pdf_text observed=2026-08-07T11:29:55.165289Z digest=sha256:6e5c0e6a591a01f98ef7da9480c17c479bc9b734061c3604774fc88f556e52a4

Observation 2373d17b-2d33-49eb-9fca-d0ce8597398d · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Segformer: Simple and efficient design for semantic segmentation with transformers

Reference 62

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source=pdf_text observed=2026-08-07T11:29:55.172245Z digest=sha256:88eeb2ebae2480de168a24f2d0ad511d0fb06678b57f97b09ff50c195dbf2c63

Observation 1a411966-bc35-485a-a6b7-e4dd50aebeae · outbound

This paper cites A fourier-based framework for domain generalization.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation A fourier-based framework for domain generalization

Reference 63

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source=pdf_text observed=2026-08-07T11:29:55.181512Z digest=sha256:c26fe417e9819c8cba84b61ac6894a3d1e494d9c93e1654cdadcc73929da37da

Observation 61436ff2-bb68-4eb2-85ac-698a1a73ff4c · outbound

This paper cites A versatile framework for continual test-time domain adaptation: Balancing discriminability and generalizability.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation A versatile framework for continual test-time domain adaptation: Balancing discriminability and generalizability

Reference 64

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:29:55.189186Z digest=sha256:ea80ae1f5d1fa0d4a82fc2a9564ffc3e986200ef207a8350871699cf6b9572eb

Observation 83e2702d-cb08-4f5a-9155-015a6463ee3f · outbound

This paper cites Fda: Fourier domain adaptation for semantic segmentation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Fda: Fourier domain adaptation for semantic segmentation

Reference 65

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raw_fallback, observed 2026-08-07T11:29:55.908144Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T11:29:55.198348Z digest=sha256:bc8b97ec5d3cdceb792a03880cb56f915dabe9b37b5e8b12bce108211bbd5414

Observation 1c3588de-595c-4a99-960d-34455e367b75 · outbound

This paper cites Robust test-time adaptation in dynamic scenarios.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Robust test-time adaptation in dynamic scenarios

Reference 66

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source=pdf_text observed=2026-08-07T11:29:55.208256Z digest=sha256:56cabbacef255ed571d07fdb1c4ffd8b09362ebcf1befc7c5bcac86b30f2329c

Observation f0a4b83c-aca9-436a-809e-36875e3f0fbe · outbound

This paper cites Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation

Reference 67

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local_arxiv, observed 2026-08-07T11:29:55.437406Z

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=2026-08-07T11:29:55.220068Z digest=sha256:65e93e69a2107c1d6e45031f5f409ef68bda42ad37f401497c1e9ee64000e25a

Observation 1d6679d3-9e02-45e2-a78d-90682c5b83a6 · outbound

This paper cites Rethinking precision of pseudo label: Test-time adaptation via complementary learning.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Rethinking precision of pseudo label: Test-time adaptation via complementary learning

Reference 68

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raw_fallback, observed 2026-08-07T11:29:55.869053Z

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=2026-08-07T11:29:55.228769Z digest=sha256:9546f973a899e6d732955566d37158674fcbf13f5473e19ef3f1f4dacf730aee

Observation 5554507d-20ee-4301-bb4c-15a5c496824f · outbound

This paper cites Memo: Test time robustness via adaptation and augmentation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Memo: Test time robustness via adaptation and augmentation

Reference 69

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:29:55.236703Z digest=sha256:d1967826c041585fb28e92ea3d88bdd362b3b3bf1a7bb53aba2d9719e5162133

Observation e255f717-7a52-42b6-a012-73834db58d21 · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 70

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source=pdf_text observed=2026-08-07T11:29:55.244527Z digest=sha256:0ca1cb1b0b3bd4e0bba2e5fbce95e7b201f5a1cac8959093dcfd2747f3fa2cf1

Observation a762bb59-e59a-434f-bd56-333d9b96c26d · outbound

This paper cites DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation

Reference 71

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source=pdf_text observed=2026-08-07T11:29:55.254321Z digest=sha256:7f57bbc2adc8ccccfdd7dd2682eba1a1585003637fb53ef7e578e5c2fba9e66e

Observation 97c79a1d-065b-44d0-9a56-4ff59f060fb9 · outbound

This paper cites Ot-vp: Optimal transport-guided visual prompting for test-time adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation Ot-vp: Optimal transport-guided visual prompting for test-time adaptation

Reference 72

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raw_fallback, observed 2026-08-07T11:29:55.834531Z

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=2026-08-07T11:29:55.261297Z digest=sha256:617f2ca29ec056280d7303874f95bf6c1850c10872068690b0281e52611155f7

Observation 56c08329-6e5b-4834-bffe-a1b0c4581dd2 · outbound

This paper cites DELTA: degradation-free fully test-time adaptation.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation DELTA: degradation-free fully test-time adaptation

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T11:29:55.267643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:29:55.267643Z digest=sha256:567cd5dab46364d24e683c8b3b659e92f52c2ba786b2aa8a5ae7fc99a3aa48cd

Observation 384d46e2-adb1-42c1-a338-cce8efe402c8 · outbound

This paper cites 10-round.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation 10-round

Reference 74

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T11:29:55.815840Z

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=2026-08-07T11:29:55.274473Z digest=sha256:36692c45fa6b2c4be4851906fe8f034a1dc8ff518c03c9eeed5e6b6d4cab6128

Pith citing papers

Observation 38c93f3f-ca56-4057-b19f-42da900a6972 · inbound

Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging cites this paper.

Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:48:12.691551Z

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=2026-05-20T10:47:38.553051Z digest=sha256:f2272d60946ff82d86ca7214262f405a17ee6dd65f9865c2914ca22ef286ef05