Paper Citation Record · LEDGER

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model

As of 22 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2607.03810.

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

pith.paper-citation-record.v1
2607.03810 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T23:48:25.354479Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation 38d005b6-645f-4a3d-9425-568fd492b652 · outbound

This paper cites an unresolved cited work.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22727551-23e3-4be0-9fdf-b07d5982e364 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 78ee19eb-1894-4efa-bbe8-09c063ed2e24 · outbound

This paper cites Do- main adaptation for semantic segmentation with maximum squares loss.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Do- main adaptation for semantic segmentation with maximum squares loss

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 53a5cdc6-eef8-4ec7-8ae5-4bbb5aa5f2a9 · outbound

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

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model The cityscapes dataset for semantic urban scene understanding

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 37d7217c-d3cc-47ef-b6ea-3288e0ff6559 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.IEEE Signal Processing Maga- zine, 29(6):141–142, 2012.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model The mnist database of handwritten digit images for machine learning research.IEEE Signal Processing Maga- zine, 29(6):141–142, 2012

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 68e4336b-a30c-4db1-8ae6-27f7a2220931 · outbound

This paper cites Robust mean teacher for continual and gradual test-time adaptation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Robust mean teacher for continual and gradual test-time adaptation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3832f88-3579-42ee-8fba-2bd532249f93 · outbound

This paper cites Uncertainty reduction for model adaptation in semantic segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Uncertainty reduction for model adaptation in semantic segmentation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eb8b620-8f45-4ae8-af62-ad177be1c940 · outbound

This paper cites Back to the source: Diffusion- driven adaptation to test-time corruption.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Back to the source: Diffusion- driven adaptation to test-time corruption

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd64365a-07b4-4ce6-ac6a-87ced91a29c6 · outbound

This paper cites Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d48ebf17-5c5b-436c-a6af-cec46df5b389 · outbound

This paper cites Deep residual learning for image recognition.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Deep residual learning for image recognition

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb308698-95b9-4ddc-8844-71c615d4c0ff · outbound

This paper cites Model adaptation: Historical contrastive learning for unsu- pervised domain adaptation without source data.Advances in neural information processing systems, 34:3635–3649,.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Model adaptation: Historical contrastive learning for unsu- pervised domain adaptation without source data.Advances in neural information processing systems, 34:3635–3649,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 8d565c69-50e0-4e16-b952-2364e4ea75b8 · outbound

This paper cites Multispectral pedestrian detection: Benchmark dataset and baseline.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Multispectral pedestrian detection: Benchmark dataset and baseline

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation 03af7086-971b-4277-be08-0e957592ce85 · outbound

This paper cites Video analytics dataset.https://www.ino.ca/ en/technologies/video- analyticsdataset/,.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Video analytics dataset.https://www.ino.ca/ en/technologies/video- analyticsdataset/,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation 30b9f9b1-7c37-4ec3-8d49-db987b2ed2cf · outbound

This paper cites an unresolved cited work.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7aff02a8-aa00-4441-8593-217d638a4e17 · outbound

This paper cites Deflating dataset bias us- ing synthetic data augmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Deflating dataset bias us- ing synthetic data augmentation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 0a81f2df-35d5-4960-bfbc-4093da7d971f · outbound

This paper cites Yuille, and Li Cheng.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Yuille, and Li Cheng

Reference 16

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Observation 03d5d833-33f2-4cf9-9c0e-c1eb2097625e · outbound

This paper cites YOLO by ultralytics, 2023.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model YOLO by ultralytics, 2023

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation abbe1be6-a619-47af-a97a-4043200eddaf · outbound

This paper cites Ev-tta: Test-time adaptation for event-based object recognition.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Ev-tta: Test-time adaptation for event-based object recognition

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18053736-eb52-444d-bdcb-2fe1a7975af6 · outbound

This paper cites Segment any- thing.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Segment any- thing

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36f7e7d0-eda3-4dac-8153-fba3a766705b · outbound

This paper cites A review of domain adap- tation without target labels.IEEE transactions on pattern analysis and machine intelligence, 43(3):766–785, 2019.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model A review of domain adap- tation without target labels.IEEE transactions on pattern analysis and machine intelligence, 43(3):766–785, 2019

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 351beb46-a816-4a8e-b469-454bf2ee6d24 · outbound

This paper cites Rgb-t object tracking: Benchmark and baseline.Pat- tern Recognition, 96:106977, 2019.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Rgb-t object tracking: Benchmark and baseline.Pat- tern Recognition, 96:106977, 2019

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83336615-a19f-48c6-a43f-c10af37bd4a9 · outbound

This paper cites A comprehensive survey on source-free domain adap- tation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model A comprehensive survey on source-free domain adap- tation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4229fcf1-946a-4395-bbe7-bb8263b1a7f7 · outbound

This paper cites Multi- interactive feature learning and a full-time multi-modality benchmark for image fusion and segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Multi- interactive feature learning and a full-time multi-modality benchmark for image fusion and segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1de6794-6953-4120-afdc-668bbfaf4718 · outbound

This paper cites Source-free domain adaptation for semantic segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Source-free domain adaptation for semantic segmentation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15e16146-0e1c-4a46-845a-3987fa3e928e · outbound

This paper cites Improved self-training for test-time adaptation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Improved self-training for test-time adaptation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c30446a-29ab-4540-ae4b-cb5a7f6f8d57 · outbound

This paper cites Reading digits in natural images with unsupervised feature learning.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Reading digits in natural images with unsupervised feature learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 705f7624-41a9-45ec-ad9f-c6ccd9cc81fe · outbound

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

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Efficient test-time model adaptation without forgetting

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

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Observation 4f3e85fc-71d1-4299-a778-344b59fa1f05 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Learning transferable visual models from natural language supervi- sion

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation 8885fecf-1051-45de-b497-f767456de7fe · outbound

This paper cites Playing for data: Ground truth from computer games.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Playing for data: Ground truth from computer games

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation 59abdb15-c85b-41c7-98a5-db9286496362 · outbound

This paper cites Generalization in neural networks: A broad survey.Neurocomputing, 611:128701, 2025.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Generalization in neural networks: A broad survey.Neurocomputing, 611:128701, 2025

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation f5d1850f-3218-47ad-b560-e6ac2bec8791 · outbound

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

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Acdc: The adverse conditions dataset with correspondences for se- mantic driving scene understanding

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 60371439-4d9b-4659-91ba-983c51f19e4d · outbound

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

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Ecotta: Memory-efficient continual test-time adaptation via self-distilled regularization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6601e9a1-314f-4f8e-9e2f-6e27f184aac1 · outbound

This paper cites Source- free domain adaptation with frozen multimodal foundation model.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Source- free domain adaptation with frozen multimodal foundation model

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 468b0b87-8145-46e0-a46a-5b3eca1ae30e · outbound

This paper cites Vdm-da: Virtual domain modeling for source data-free domain adap- tation.IEEE Transactions on Circuits and Systems for Video Technology, 32(6):3749–3760, 2021.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Vdm-da: Virtual domain modeling for source data-free domain adap- tation.IEEE Transactions on Circuits and Systems for Video Technology, 32(6):3749–3760, 2021

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation fe589987-0a0d-42d9-b661-1c74669ef1f8 · outbound

This paper cites Gda: Generalized diffusion for robust test-time adaptation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Gda: Generalized diffusion for robust test-time adaptation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation ced0bfc4-3b13-4a85-8935-70834d85409c · outbound

This paper cites Yolov8: A novel object detection algorithm with enhanced performance and robust- ness.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Yolov8: A novel object detection algorithm with enhanced performance and robust- ness

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation 641ce8e3-a724-4471-b157-67c88f02ed61 · outbound

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

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation ea4c87a0-9395-4dea-b9ee-32bb9b9f04e3 · outbound

This paper cites Continual test-time domain adaptation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Continual test-time domain adaptation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Observation c3e44b9b-967f-45aa-89e4-a9573d5a4e7c · outbound

This paper cites Feature alignment and uniformity for test time adap- tation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Feature alignment and uniformity for test time adap- tation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba5d128b-165e-48e8-b731-5adbe25f5150 · outbound

This paper cites Dynamically instance- guided adaptation: A backward-free approach for test-time domain adaptive semantic segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Dynamically instance- guided adaptation: A backward-free approach for test-time domain adaptive semantic segmentation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Unavailable: canonical work link unavailable.

Observation 904dc1fe-1ed1-47f4-b612-15b57725c2b2 · outbound

This paper cites Sam4udass: When sam meets un- supervised domain adaptive semantic segmentation in intel- ligent vehicles.IEEE Transactions on Intelligent Vehicles, 9 (2):3396–3408, 2023.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Sam4udass: When sam meets un- supervised domain adaptive semantic segmentation in intel- ligent vehicles.IEEE Transactions on Intelligent Vehicles, 9 (2):3396–3408, 2023

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a910baf-afea-4b61-9096-301778a75479 · outbound

This paper cites Source data-free unsupervised domain adaptation for seman- tic segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Source data-free unsupervised domain adaptation for seman- tic segmentation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34b19095-4706-4fbc-99bc-53e355b450bf · outbound

This paper cites Towards better stability and adaptabil- ity: Improve online self-training for model adaptation in se- mantic segmentation.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Towards better stability and adaptabil- ity: Improve online self-training for model adaptation in se- mantic segmentation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1db77851-2c53-4e33-af7d-f4e3586a12fa · outbound

This paper cites Fast Segment Anything.

TestMate: Test-Time Domain Adaptation Aided by Lightweight Vision Foundation Model Fast Segment Anything

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-11T23:48:25.354479Z

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Pith citing papers

No inbound Pith citation observations are available.