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Paper Citation Record · LEDGER

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment

As of 18 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 0 inbound Pith citation observations for arXiv:2506.22509.

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

pith.paper-citation-record.v1
2506.22509 v1

Coverage vector

measured 86 of 86 reference resolution

Typed states for the displayed outbound observations.

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measured 86 of 86 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

86 of 86 outbound references displayed

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External citation measurements

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Outbound references

Observation d08c52a0-b7aa-464f-95c0-2ae0733b273d · outbound

This paper cites Ntire 2017 challenge on single image super-resolution: Dataset and study.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Ntire 2017 challenge on single image super-resolution: Dataset and study

Reference 1

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Observation 5621f5a6-0016-4454-8950-4e0f13f710ae · outbound

This paper cites SegDiff: Image Segmentation with Diffusion Probabilistic Models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment SegDiff: Image Segmentation with Diffusion Probabilistic Models

Reference 2

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Observation ddbb6e7f-945d-492e-aad3-1ddfdb3b4ae1 · outbound

This paper cites Test-time adaptation for optical flow estimation using motion vec- tors.IEEE Transactions on Image Processing, 32:4977– 4988, 2023.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Test-time adaptation for optical flow estimation using motion vec- tors.IEEE Transactions on Image Processing, 32:4977– 4988, 2023

Reference 3

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Observation 10595e6a-2339-43d0-a784-d546d415e23c · outbound

This paper cites Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models

Reference 4

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Observation 858b24cd-ec90-4e95-9b5b-ba3d95d833c7 · outbound

This paper cites Analysis of representations for domain adapta- tion.Advances in neural information processing systems, 19, 2006.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Analysis of representations for domain adapta- tion.Advances in neural information processing systems, 19, 2006

Reference 5

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Observation be0bc5bf-2380-4fe7-affd-a80af50c01dd · outbound

This paper cites One-shot unsupervised do- main adaptation with personalized diffusion models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment One-shot unsupervised do- main adaptation with personalized diffusion models

Reference 6

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Observation 22215e1a-aa65-4b94-90fb-11310ae2f8f0 · outbound

This paper cites Contrastive model adaptation for cross- condition robustness in semantic segmentation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Contrastive model adaptation for cross- condition robustness in semantic segmentation

Reference 7

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Observation f3619697-bfbb-42f0-b81b-9bc513c4ecad · outbound

This paper cites A naturalistic open source movie for opti- cal flow evaluation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment A naturalistic open source movie for opti- cal flow evaluation

Reference 8

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Observation 5bcc08aa-ea56-459d-8297-c38ef80144e9 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment nuscenes: A multi- modal dataset for autonomous driving

Reference 9

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Observation fe58b432-3508-4e32-9ac5-68102b6070b0 · outbound

This paper cites Toward real-world single image super-resolution: A new benchmark and a new model.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Toward real-world single image super-resolution: A new benchmark and a new model

Reference 10

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Observation 593a2fdb-1e4e-4a5f-a3a5-e6821fde01e0 · outbound

This paper cites Progressive feature alignment for unsupervised do- main adaptation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Progressive feature alignment for unsupervised do- main adaptation

Reference 11

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Observation 8670cbef-83fe-4269-ac5f-e6b9f0eef27a · outbound

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

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Amplitude-phase recombination: Rethink- ing robustness of convolutional neural networks in frequency domain

Reference 12

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Observation cbf49ec6-66e0-4176-a715-8edc3b1e77f4 · outbound

This paper cites S2r-depthnet: Learning a generalizable depth-specific structural representation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment S2r-depthnet: Learning a generalizable depth-specific structural representation

Reference 13

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Observation 9ef0f121-38a6-4074-a59e-1ae979a81b91 · outbound

This paper cites Text-to-image diffusion mod- els are zero shot classifiers.Advances in Neural Information Processing Systems, 36:58921–58937, 2023.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Text-to-image diffusion mod- els are zero shot classifiers.Advances in Neural Information Processing Systems, 36:58921–58937, 2023

Reference 14

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Observation 56b06615-af3f-4704-9720-47e142199f05 · outbound

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

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment The cityscapes dataset for semantic urban scene understanding

Reference 15

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Observation bcb0d816-66e1-4946-a020-3a13ef217528 · outbound

This paper cites Joint distribution optimal transportation for domain adaptation.Advances in neural information pro- cessing systems, 30, 2017.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Joint distribution optimal transportation for domain adaptation.Advances in neural information pro- cessing systems, 30, 2017

Reference 16

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Observation 81c08683-536e-4434-b32f-f1aa20aa2b94 · outbound

This paper cites Domain Adaptation for Visual Applications: A Comprehensive Survey.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Domain Adaptation for Visual Applications: A Comprehensive Survey

Reference 17

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Observation 2716d3f4-b48e-4c81-bc37-8d0ec7150ce3 · outbound

This paper cites Open-DDVM: A Reproduction and Extension of Diffusion Model for Optical Flow Estimation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Open-DDVM: A Reproduction and Extension of Diffusion Model for Optical Flow Estimation

Reference 18

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Observation a6229ce5-1eb0-4a6b-9c85-3134c41c9064 · outbound

This paper cites Training generative neural networks via Maximum Mean Discrepancy optimization.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Training generative neural networks via Maximum Mean Discrepancy optimization

Reference 19

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Observation 983f1c99-4323-4425-833f-feaa658196f2 · outbound

This paper cites A brief review of domain adaptation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment A brief review of domain adaptation

Reference 20

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Observation f817344a-296e-417f-afb4-996d0a1579be · outbound

This paper cites Virtual worlds as proxy for multi-object tracking anal- ysis.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Virtual worlds as proxy for multi-object tracking anal- ysis

Reference 21

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Observation 8d2c328e-9f37-4cf4-afa2-bff39724b06d · outbound

This paper cites Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016

Reference 22

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Observation 79f90f1d-71c7-49ac-a5fc-81842e49e766 · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 23

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Observation 962be878-d998-4072-a208-d25d6e272c4d · outbound

This paper cites Cross Domain Generative Augmentation: Domain Generalization with Latent Diffusion Models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Cross Domain Generative Augmentation: Domain Generalization with Latent Diffusion Models

Reference 24

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Observation 057b51cc-de30-4cde-b7b1-6639a0a67464 · outbound

This paper cites Classifier-Free Diffusion Guidance.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Classifier-Free Diffusion Guidance

Reference 25

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Observation 39751d7e-35e3-4045-9577-abc1bea3c408 · outbound

This paper cites Cascaded diffu- sion models for high fidelity image generation.Journal of Machine Learning Research, 23(47):1–33, 2022.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Cascaded diffu- sion models for high fidelity image generation.Journal of Machine Learning Research, 23(47):1–33, 2022

Reference 26

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Observation c185016a-95e0-45cf-bcd5-15cba5724e57 · outbound

This paper cites Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation

Reference 27

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Observation 84820182-5f2a-4d5f-9e5d-97f1a68066f3 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Arbitrary style transfer in real-time with adaptive instance normalization

Reference 28

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Observation 00772ae5-e8e3-4de9-8772-3d47b9a2d863 · outbound

This paper cites Dpbridge: La- tent diffusion bridge for dense prediction.arXiv preprint arXiv:2412.20506, 2024.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Dpbridge: La- tent diffusion bridge for dense prediction.arXiv preprint arXiv:2412.20506, 2024

Reference 29

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Observation 5ed75a27-68d0-44a3-b188-98e55ce3f139 · outbound

This paper cites Ddp: Diffusion model for dense visual prediction.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Ddp: Diffusion model for dense visual prediction

Reference 30

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Observation 6a6e5bbb-7964-41aa-ae3d-c4cd595788ff · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 31

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Observation 32c7d410-c270-43e5-a0c5-19ab65eb5259 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Musiq: Multi-scale image quality transformer

Reference 32

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Observation af0e54d9-58ab-4312-8972-801de47fab64 · outbound

This paper cites Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach

Reference 33

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Observation 2e079107-5f74-4714-9c68-91a89fd435bc · outbound

This paper cites Semi-supervised do- main adaptation via selective pseudo labeling and progres- sive self-training.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Semi-supervised do- main adaptation via selective pseudo labeling and progres- sive self-training

Reference 34

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raw_fallback, observed 2026-08-06T22:46:21.440246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.721273Z digest=sha256:a2da962e4456d6353cbbf150571bc4461e5607faf54329087791e3480ef14d57

Observation 56807980-ffec-4631-933b-0e14962c9ee9 · outbound

This paper cites Ex- ploiting diffusion prior for generalizable dense prediction.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Ex- ploiting diffusion prior for generalizable dense prediction

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.424726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.727840Z digest=sha256:3355dba073be0c44d4c8fc0508c52a344d6705f69eaecd4eb1c40db3bc093ad2

Observation f1b0ddb5-b3aa-4d30-b6a6-48a36e860488 · outbound

This paper cites Your diffusion model is secretly a zero-shot classifier.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Your diffusion model is secretly a zero-shot classifier

Reference 36

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no resolver link, observed 2026-08-06T22:46:19.732477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.732477Z digest=sha256:8e9ab05be9aa144be4139418a2644d1d17c21c96046a768698b7ab72fed7cc64

Observation ac10a987-d80f-4a33-87a3-04d6cb00b29c · outbound

This paper cites Maximum density divergence for domain adaptation.IEEE transactions on pattern analysis and machine intelligence, 43(11):3918–3930, 2020.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Maximum density divergence for domain adaptation.IEEE transactions on pattern analysis and machine intelligence, 43(11):3918–3930, 2020

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.399451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.737454Z digest=sha256:3136412516b246de46a0966c7a49253c42a4e1690acaa5f124283b39ef1f3645

Observation 86adab34-8262-4fcb-be91-487012aff1c0 · outbound

This paper cites Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps

Reference 38

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no resolver link, observed 2026-08-06T22:46:19.742670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.742670Z digest=sha256:3c5938a8d111d02af51b0a1553bec50a6a2619cfa1d6fa5fb01ef0d2ddeaeeda

Observation 3ec8d72f-5a72-42d0-99f8-a17d3167d682 · outbound

This paper cites Unsupervised domain adap- tation with progressive adaptation of subspaces.Pattern Recognition, 132:108918, 2022.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Unsupervised domain adap- tation with progressive adaptation of subspaces.Pattern Recognition, 132:108918, 2022

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.381814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.747798Z digest=sha256:44c6c70ecb4e917f4a2d0696f495d61fec5433dedeb75126e4993df3dbd457de

Observation 47f62d11-b81a-4830-9b01-3a66af7cfa53 · outbound

This paper cites Test- time domain adaptation for monocular depth estimation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Test- time domain adaptation for monocular depth estimation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.365310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.753568Z digest=sha256:1a55ccea6678641b8cc99ea09ab14748dfae385c31240e3dfa65a65b1948c70d

Observation ff04ac35-fe92-41e1-871a-1fe3fdbfdfda · outbound

This paper cites Swinir: Image restoration us- ing swin transformer.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Swinir: Image restoration us- ing swin transformer

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.758708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.758708Z digest=sha256:f316d67836e2eb86963facbae7c7a72ca0189040223811adb0cdddb6aee97c9d

Observation 8bc73fb4-5e6d-4dbd-84f2-d8f90597e20b · outbound

This paper cites Common diffusion noise schedules and sample steps are flawed.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Common diffusion noise schedules and sample steps are flawed

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.334171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.764191Z digest=sha256:11f694bd7a30c1a4a2512f3f281e32e645116bb9227cf1b839411d09ed0356fe

Observation adbd9662-aa1b-4f7d-b8f8-6c658a14ff5c · outbound

This paper cites Diff- bir: Toward blind image restoration with generative diffusion prior.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Diff- bir: Toward blind image restoration with generative diffusion prior

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.312149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.770663Z digest=sha256:07ec6b61ae7b81310fc734171a3810ca3ab2cae5e024aa7fc5e9c2fabf708965

Observation cb40bd47-23d7-48d2-b85f-7e1be2c23021 · outbound

This paper cites Stability and generalization in structured prediction.Journal of Machine Learning Research, 17(221):1–52, 2016.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Stability and generalization in structured prediction.Journal of Machine Learning Research, 17(221):1–52, 2016

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.293362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.776719Z digest=sha256:ea47651aa23da8f2cef96b702ffba955bea7d4a355c883ddb1465d4eaf84f6b6

Observation b14e9997-08d1-4f67-b9e0-7976d4653766 · outbound

This paper cites Conditional adversarial domain adapta- tion.Advances in neural information processing systems, 31, 2018.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Conditional adversarial domain adapta- tion.Advances in neural information processing systems, 31, 2018

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.277255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.781617Z digest=sha256:ff6ccc09d893d2032a0d5190489e27545d2cd7dc85a8adb5b5ddc4ee79ec1b42

Observation b1232960-8f34-4bd9-a88c-34424cee6acb · outbound

This paper cites Desc: Domain adaptation for depth estimation via semantic con- sistency.International Journal of Computer Vision, 131(3): 752–771, 2023.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Desc: Domain adaptation for depth estimation via semantic con- sistency.International Journal of Computer Vision, 131(3): 752–771, 2023

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.261925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.788154Z digest=sha256:85b036cd88fb9d345bc42cdfee9a0591068143f1eb57d3c24e6b6a04c74db9a2

Observation 996f0244-af51-4585-b02b-b77891c58d69 · outbound

This paper cites Flowdiffuser: Advancing optical flow estimation with diffusion models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Flowdiffuser: Advancing optical flow estimation with diffusion models

Reference 47

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unresolved
no resolver link, observed 2026-08-06T22:46:19.793897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.793897Z digest=sha256:a1219a52e9a966a62b807c03ed3a6bc633bf6ddfe19ff05793b403a387bdfb28

Observation 56d1d5d6-4d1c-4e04-8062-375107f0d92c · outbound

This paper cites 1 year, 1000 km: The oxford robotcar dataset.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment 1 year, 1000 km: The oxford robotcar dataset

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.231671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.800057Z digest=sha256:d7200f65f4bfd09cd6ae919256fb35ee5033b995a7cbece2d4242c3499881890

Observation 361155d2-3b2e-42d0-bcc2-196b30bcc4a6 · outbound

This paper cites Generalization by adaptation: Diffusion-based domain extension for domain-generalized semantic segmentation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Generalization by adaptation: Diffusion-based domain extension for domain-generalized semantic segmentation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.213991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.805801Z digest=sha256:e43e40e93b8108e95748d32283d3a0fede1b8847a009b23ce3c4f6b3dd7552c7

Observation 98654895-5a7b-4405-afa8-af7a454aba1a · outbound

This paper cites Elucidating the Exposure Bias in Diffusion Models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Elucidating the Exposure Bias in Diffusion Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.811786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.811786Z digest=sha256:a370bdf1b3ad60e993a1cccae4c56d8d92367e78e6b73dfad08ea67b3d503f29

Observation 04517ec6-5a21-4a97-8a3f-50e8ad323294 · outbound

This paper cites Input Perturbation Reduces Exposure Bias in Diffusion Models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Input Perturbation Reduces Exposure Bias in Diffusion Models

Reference 51

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no resolver link, observed 2026-08-06T22:46:19.818201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.818201Z digest=sha256:4273078ad2411d6301a3926c29693de05fa7218cdfe3ca8463fe503226ceb65e

Observation c356b1e4-534a-4269-8b9a-cca09be9f826 · outbound

This paper cites an unresolved cited work.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Unresolved cited work

Reference 52

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unresolved
raw_fallback, observed 2026-08-06T22:46:21.196070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.824545Z digest=sha256:3884a3217ec863dfb8d040a4062cb5b54bbdc2ac38269678c7f2327f927b631c

Observation df95d1da-ec04-4498-a28e-e21a4167da97 · outbound

This paper cites Vi- sion transformers for dense prediction.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Vi- sion transformers for dense prediction

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.178419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.837584Z digest=sha256:adeb1b83f5ef5ee1a0fd66f2558e0151c312d65214b202dff2df28dbc9ec7de2

Observation c114f3ad-8140-49e6-b949-c7bb75ceb797 · outbound

This paper cites Multi-step denoising scheduled sampling: Towards alleviating exposure bias for diffusion models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Multi-step denoising scheduled sampling: Towards alleviating exposure bias for diffusion models

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.161220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.843282Z digest=sha256:72215feac7f61ab1b015a2ebf41cb82285a2c38f76934d57791d4c1955d932eb

Observation 748dc212-6971-4fa8-9571-dc97dc0665c9 · outbound

This paper cites Hypersim: A photorealistic syn- thetic dataset for holistic indoor scene understanding.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Hypersim: A photorealistic syn- thetic dataset for holistic indoor scene understanding

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.849864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.849864Z digest=sha256:7e15e570558530733b01514d6f862be96df3f08e384b00b03b587e0184e6ad84

Observation 909e9647-0c46-4578-b6db-df14a9c85007 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment High-resolution image synthesis with latent diffusion models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.855302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.855302Z digest=sha256:81daefb0e78305e840e33e54659ea4e467c66f6e41b26bbb1cc61c90a81af39a

Observation 23af3349-460c-4459-a54b-1f962581e4f0 · outbound

This paper cites Universal domain adaptation through self supervi- sion.Advances in neural information processing systems, 33:16282–16292, 2020.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Universal domain adaptation through self supervi- sion.Advances in neural information processing systems, 33:16282–16292, 2020

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.124185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.860108Z digest=sha256:efab5d14e7c9c695027e28dff44e5daa5b4a344c18119c31201e76ce22244173

Observation 268e47b6-1d58-4516-90ed-5762eba6b3d4 · outbound

This paper cites an unresolved cited work.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:46:21.105655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.864867Z digest=sha256:2fbae20cdffcc5b04f9656c038654d9a1928dec4cd76659ba4b27f8bfcd6d30f

Observation a747f126-8f90-4cb3-8205-ac4259192876 · outbound

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

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Acdc: The adverse conditions dataset with correspondences for semantic driving scene understanding

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.090591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.870073Z digest=sha256:9fd808c2625b759f099aba395ac350921a2c23748883362b094e6c2fd6974f1a

Observation 4b34a87e-4250-4b7e-9d89-af488ac0760a · outbound

This paper cites The surprising effectiveness of diffusion models for optical flow and monocular depth estimation.Advances in Neural Information Processing Systems, 36:39443–39469, 2023.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment The surprising effectiveness of diffusion models for optical flow and monocular depth estimation.Advances in Neural Information Processing Systems, 36:39443–39469, 2023

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.073442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.874907Z digest=sha256:d7c301772a4c73b71d2dfdf9a26d8455f006b9f273158a72dcdd950febe2c399

Observation 6b30d417-a09a-4b36-a4d1-85399315bb29 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294, 2022.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294, 2022

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.879727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.879727Z digest=sha256:262a9b1e6f16a22c9efe66f69e83672434e832999432200423f23f964ce25cea

Observation 0889ca79-dcd9-4641-83a1-e5b0b2464a49 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Indoor segmentation and support inference from rgbd images

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.045805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.886310Z digest=sha256:69304834278e5188079742e04961bde5a467ab6f82fefefebab08f917e851c9a

Observation eec69955-e386-4bb9-90ce-d24c92cdcc1c · outbound

This paper cites Diffusion Guided Domain Adaptation of Image Generators.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Diffusion Guided Domain Adaptation of Image Generators

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:46:20.139813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.891803Z digest=sha256:a35728a907acebd6353aece88f14d59d3033de94ca1dfd2d62f4f329ccf22ef6

Observation aa169ab3-d830-4d59-b287-1eb309eb2695 · outbound

This paper cites Autoflow: Learning a better training set for optical flow.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Autoflow: Learning a better training set for optical flow

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.029942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.897917Z digest=sha256:a3c4eb88488c4197389073dc74b29a2dfe264c70a0a7ea9f4e48a423834d05e2

Observation e4898237-482d-436a-8fc8-b453c1885907 · outbound

This paper cites Unsupervised Domain Adaptation through Self-Supervision.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Unsupervised Domain Adaptation through Self-Supervision

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.903728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.903728Z digest=sha256:0373f3af308c9435c5bc2382a7711cfe82fa0f8acf228f797f1184d7b323aafe

Observation 13890410-d25c-4b70-9a17-0d5fe242f842 · outbound

This paper cites Distortion-aware convolutional filters for dense prediction in panoramic images.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Distortion-aware convolutional filters for dense prediction in panoramic images

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:21.014094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.909802Z digest=sha256:745d6edb52759e1306c9c84ccdd686b2010726a0a01a2570b8362fc3ab0fb3d4

Observation acc29d2e-d527-4322-a40c-8333a2414ef4 · outbound

This paper cites Ntire 2017 challenge on single image super-resolution: Methods and results.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Ntire 2017 challenge on single image super-resolution: Methods and results

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.998254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.916811Z digest=sha256:03f66137be9a82c0e36ba27fa0ce99b5e8742cf34e839ae93a45c183aea4f11d

Observation 7a39be25-dd89-45de-b205-cbd6eaac3d61 · outbound

This paper cites Dacs: Domain adaptation via cross- domain mixed sampling.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Dacs: Domain adaptation via cross- domain mixed sampling

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.982751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.925305Z digest=sha256:913c42cad56fd14f3fb428f6b2811fc6f25c3ae8344d8dff0dae7646a936cd39

Observation 763f8b0b-c150-44b5-9e4a-1e0f38b817b1 · outbound

This paper cites Adversarial discriminative domain adaptation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Adversarial discriminative domain adaptation

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.931176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.931176Z digest=sha256:483d8e02b143b1285a0fe58239f315c63387b57a1f85602844235b8f6a25ea01

Observation ef5f7697-3834-4581-9591-914aefc95741 · outbound

This paper cites Undaf: A general unsupervised domain adapta- tion framework for disparity or optical flow estimation.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Undaf: A general unsupervised domain adapta- tion framework for disparity or optical flow estimation

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.957834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.936529Z digest=sha256:1a65d3cab8b8e4605137ef933e929b98cf878836e21a7f6b1ca7e561c4787a42

Observation 24763833-f11c-442f-8a66-7c3c98003eec · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, 132(12):5929–5949, 2024.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, 132(12):5929–5949, 2024

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.939485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.941714Z digest=sha256:c646a1e54041e045f5cc4dab4699d8cf9e797e6805b1d271cba57c6d94952eca

Observation 953e67b4-75a1-44a4-9c9f-6cc9ca7a8727 · outbound

This paper cites Deep visual domain adapta- tion: A survey.Neurocomputing, 312:135–153, 2018.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Deep visual domain adapta- tion: A survey.Neurocomputing, 312:135–153, 2018

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.923293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.946998Z digest=sha256:922666ccf975953db24e3271f1c4417093fa24056dd299efcedf0c841533ab67

Observation bde136e7-e78e-4288-8457-01585f8980ec · outbound

This paper cites Rethinking maxi- mum mean discrepancy for visual domain adaptation.IEEE Transactions on Neural Networks and Learning Systems, 34 (1):264–277, 2021.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Rethinking maxi- mum mean discrepancy for visual domain adaptation.IEEE Transactions on Neural Networks and Learning Systems, 34 (1):264–277, 2021

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.906268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.952504Z digest=sha256:c4db90dc86a361c45f3206ed0f0e0fb4dfc0b1d43d199007179872b0db68a657

Observation 0481fa58-fe45-4dea-9cb9-eb496c569971 · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Pyramid vision transformer: A versatile backbone for dense prediction without convolutions

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.958446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.958446Z digest=sha256:5a20cdde50668e95a6a11df0d4d68822af35a012dab659f5e891c7dbdc4a8e01

Observation 9f2c88ab-a477-45b9-8eb8-c5014c286691 · outbound

This paper cites Component divide- and-conquer for real-world image super-resolution.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Component divide- and-conquer for real-world image super-resolution

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.879455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.964225Z digest=sha256:e4ab6088efaa150027643734f77ec8885cbfb10b7b9358fbff33c1586888ac5f

Observation d683b409-2957-4fae-8dd9-a908e423fa79 · outbound

This paper cites Multi-block domain adaptation with central mo- ment discrepancy for fault diagnosis.Measurement, 169: 108516, 2021.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Multi-block domain adaptation with central mo- ment discrepancy for fault diagnosis.Measurement, 169: 108516, 2021

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.861538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.969199Z digest=sha256:c9681be7ecd033a9a66ba8053b54cdbce1d47a3a891bcc20b12c08d9d52914e6

Observation 81ef28ee-e9ae-4e07-9850-5fb4b7df9837 · outbound

This paper cites Maniqa: Multi-dimension attention network for no-reference image quality assessment.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.843127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.974014Z digest=sha256:867d2c649f316712bd26edd0a4461b899415b8469924bbfdc8be9f951d0bc118

Observation 9934f0c3-48e3-4ae8-bf81-7f7090efb6f4 · outbound

This paper cites Learning to recover 3d scene shape from a single image.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Learning to recover 3d scene shape from a single image

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.823766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.980069Z digest=sha256:d0f70279c662444be730fb448afe257b862eef38a854e124c3bee3df4755408f

Observation f65ee1c2-1f13-4f9a-8e5f-9d3845e9a541 · outbound

This paper cites Optical flow domain adaptation via target style trans- fer.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Optical flow domain adaptation via target style trans- fer

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.805665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:19.984978Z digest=sha256:75511b3bf90eb603855777271c25e2e49ff1cef6da08675a5f89a217aacf994a

Observation f18e451b-8161-46c2-b772-7e2613bbefce · outbound

This paper cites HRFormer: High-Resolution Transformer for Dense Prediction.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment HRFormer: High-Resolution Transformer for Dense Prediction

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.990624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.990624Z digest=sha256:04a3026ee666ccca6e30804976539856a4c26997a20f9b821c17a2ad56f4b6f2

Observation 25a17991-d17f-41ae-ac74-f0d3c332e7db · outbound

This paper cites Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.995918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.995918Z digest=sha256:20ad9b33d7eb0f63524af0c2f1ec1c3b877f675c279fc7a87c2de070b9402f1f

Observation 01eac61a-330e-4ab4-b0d4-fde0c6667b18 · outbound

This paper cites Three things we need to know about trans- ferring stable diffusion to visual dense prediction tasks.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Three things we need to know about trans- ferring stable diffusion to visual dense prediction tasks

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.787576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:20.001692Z digest=sha256:20c0ced3d60f78310d3d3d442dcd4e732fa05afbf5f1d566cec778b90f5a5a6a

Observation 2cf1e53a-5976-48cb-b8b5-0bc6a5d832cf · outbound

This paper cites Optical flow in the dark.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Optical flow in the dark

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.769403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:20.007206Z digest=sha256:dd6111158baa3ae4e7dd02b0358f2f6bfce8d27d8520c77cbc72a6779e36de5a

Observation fe121ffa-2503-4b93-b779-9e9c045c78e0 · outbound

This paper cites Unsu- pervised cumulative domain adaptation for foggy scene op- tical flow.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Unsu- pervised cumulative domain adaptation for foggy scene op- tical flow

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.752411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:20.014264Z digest=sha256:5e9e9bad864a5c6ccd731db7ef37b56675b5f8c3da7a814e9dddaaf1f109e0e0

Observation 50f858cf-6d67-4507-adb1-27a0a605c948 · outbound

This paper cites Conditional text image generation with diffu- sion models.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Conditional text image generation with diffu- sion models

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.734596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:20.020392Z digest=sha256:ca3414ed1f1fbd644464f53d21fce6ba3d61d615e6b6b262b424aaf9dd252fd0

Observation 2c6bd0c7-e9f5-40e8-8b4b-d8169582cf53 · outbound

This paper cites Flowie: Efficient image enhancement via rectified flow.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment Flowie: Efficient image enhancement via rectified flow

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:46:20.714301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:46:20.024862Z digest=sha256:ba923571f0651e03f96e20e9783fea1875f65857ed7de187e6961bf153e6716c

Pith citing papers

No inbound Pith citation observations are available.