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Paper Citation Record · LEDGER

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability

As of 9 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 1 inbound Pith citation observation for arXiv:2506.21042.

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

pith.paper-citation-record.v1
2506.21042 v2

Coverage vector

measured 90 of 90 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:43:41.918011Z

measured 91 of 91 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 2026-08-09T00:37:40.360050Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T00:37:40.393910Z

Reference resolution

90 of 90 outbound references displayed

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  • verified fuzzy58
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ed6af72-4bad-4fef-afe5-bcbcd206d4a8 · outbound

This paper cites Metareg: Towards domain generalization using meta- regularization.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Metareg: Towards domain generalization using meta- regularization

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 12e3566a-95bf-492b-b214-2f7de0492927 · outbound

This paper cites Label-efficient se- mantic segmentation with diffusion models.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Label-efficient se- mantic segmentation with diffusion models

Reference 2

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Observation 63b0147c-59d8-48d5-9601-22e8d5ff8a10 · outbound

This paper cites Contrastive mean teacher for domain adaptive ob- ject detectors.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Contrastive mean teacher for domain adaptive ob- ject detectors

Reference 3

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Unavailable: canonical work link unavailable.

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Observation df3586a9-0667-46af-aa64-a8b2fe959a16 · outbound

This paper cites Harmonizing transferability and discrim- inability for adapting object detectors.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Harmonizing transferability and discrim- inability for adapting object detectors

Reference 4

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Observation 3e0a3b7d-71b6-4fd6-94e7-f454ed4fe2f3 · outbound

This paper cites Dual bipartite graph learning: A general approach for domain adaptive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Dual bipartite graph learning: A general approach for domain adaptive object detection

Reference 5

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Unavailable: canonical work link unavailable.

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Observation 629ec812-5e21-4321-ae8d-22784da19e04 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4c986d7d-3ce1-4bc4-b8d5-9981cb365dc5 · outbound

This paper cites Geodiffusion: Text- prompted geometric control for object detection data gen- eration.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Geodiffusion: Text- prompted geometric control for object detection data gen- eration

Reference 7

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Source-reported events for the cited work

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Observation bb8961e3-45a3-4f32-b58f-cf83a4f5f8a3 · outbound

This paper cites Learning domain adaptive object detection with probabilistic teacher.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Learning domain adaptive object detection with probabilistic teacher

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d0d1ad88-d6de-402e-8fec-42669cc7ed7b · outbound

This paper cites Domain adaptive faster r-cnn for object de- tection in the wild.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Domain adaptive faster r-cnn for object de- tection in the wild

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c124862c-9e18-4f96-a8c6-864947f7d24b · outbound

This paper cites Scale-aware domain adap- tive faster r-cnn.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Scale-aware domain adap- tive faster r-cnn

Reference 10

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Observation 5f5a21bd-b64a-4951-9080-587db44d2ac5 · outbound

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

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability The cityscapes dataset for semantic urban scene understanding

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e70e3f41-123d-47a6-b06b-a62fc5f460c9 · outbound

This paper cites Randaugment: Practical automated data augmen- tation with a reduced search space.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Randaugment: Practical automated data augmen- tation with a reduced search space

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 06e7b7bf-93d5-4016-a8d7-f876bc136659 · outbound

This paper cites Improving single domain-generalized object detection: A focus on diversification and alignment.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Improving single domain-generalized object detection: A focus on diversification and alignment

Reference 13

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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 dc4466e5-2de3-44d0-bcfb-31031bd66799 · outbound

This paper cites Un- biased mean teacher for cross-domain object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Un- biased mean teacher for cross-domain object detection

Reference 14

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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 7c34e552-476c-4e1b-bbee-7e07099f54cf · outbound

This paper cites Harmo- nious teacher for cross-domain object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Harmo- nious teacher for cross-domain object detection

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 863b75ac-8e63-482b-89e9-90f62a90f1e6 · outbound

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

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 62dcf4b6-b227-41d9-b491-7fb473da4ca4 · outbound

This paper cites Learning to learn with variational information bottleneck for domain general- ization.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Learning to learn with variational information bottleneck for domain general- ization

Reference 17

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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 c2ca3da5-98aa-4f21-93e1-254b62bb585b · outbound

This paper cites Davimnet: Ssms-based do- main adaptive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Davimnet: Ssms-based do- main adaptive object detection

Reference 18

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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 3d5d76ed-db0e-470c-a417-f8878745aefb · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ee098c4a-8111-41cd-8450-1f835de32627 · outbound

This paper cites The pascal visual object classes (voc) challenge.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability The pascal visual object classes (voc) challenge

Reference 20

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Observation 0759d030-8bc8-4955-ae21-5f0ac720b5d8 · outbound

This paper cites Generative adversarial networks.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Generative adversarial networks

Reference 21

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Observation 300017e8-c5bc-467e-b930-141fa2fb5d73 · outbound

This paper cites Dsca: A dual semantic correlation align- ment method for domain adaptation object detection.Pattern Recognition, 150:110329, 2024.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Dsca: A dual semantic correlation align- ment method for domain adaptation object detection.Pattern Recognition, 150:110329, 2024

Reference 22

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Source-reported events for the cited work

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Observation 4eb46b46-fe29-4f88-9104-11f4a62a3a51 · outbound

This paper cites Dif- fusion domain teacher: Diffusion guided domain adaptive object detector.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Dif- fusion domain teacher: Diffusion guided domain adaptive object detector

Reference 23

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

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Observation 9e15f4c8-8ddc-4aae-8932-1143239b5da9 · outbound

This paper cites Generalized diffusion detector: Mining robust features from diffusion models for domain-generalized de- tection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Generalized diffusion detector: Mining robust features from diffusion models for domain-generalized de- tection

Reference 24

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

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Observation eb5f705b-8e11-4479-9f83-8159626ef3bb · outbound

This paper cites Deep residual learning for image recognition.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Deep residual learning for image recognition

Reference 25

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Observation cb9675c0-083a-4a60-a1e3-d827c4a930d9 · outbound

This paper cites Cross domain object detection by target-perceived dual branch distillation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Cross domain object detection by target-perceived dual branch distillation

Reference 26

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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 bf91c686-6074-4f89-9640-fe18826b8fe9 · outbound

This paper cites Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance

Reference 27

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Source-reported events for the cited work

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Observation 77900a47-8bc6-4395-882b-d8b5285f6882 · outbound

This paper cites Denoising dif- fusion probabilistic models.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Denoising dif- fusion probabilistic models

Reference 28

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Observation 601ad6a6-6244-4e34-b19a-ee85e0dc1422 · outbound

This paper cites Denoising dif- fusion probabilistic models.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Denoising dif- fusion probabilistic models

Reference 29

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Unavailable: canonical work link unavailable.

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Observation b06e18de-df36-4550-9947-6a85411f3a91 · outbound

This paper cites Stylemix: Sep- arating content and style for enhanced data augmentation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Stylemix: Sep- arating content and style for enhanced data augmentation

Reference 30

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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 a3b741d1-8649-4d75-8c66-dac619398c15 · outbound

This paper cites Mic: Masked image consistency for context- enhanced domain adaptation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Mic: Masked image consistency for context- enhanced domain adaptation

Reference 31

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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 07423774-a53b-4bd9-95d2-8197e7cd8c5d · outbound

This paper cites Every pixel matters: Center-aware feature alignment for domain adaptive object detector.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Every pixel matters: Center-aware feature alignment for domain adaptive object detector

Reference 32

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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 cf83fa94-8359-4a43-9e93-2e6e9aa21067 · outbound

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

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Fsdr: Frequency space domain randomization for domain generalization

Reference 33

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

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Observation 09da3206-0ffd-48af-a861-735fb5a41ec6 · outbound

This paper cites Cross-domain weakly-supervised object de- tection through progressive domain adaptation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Cross-domain weakly-supervised object de- tection through progressive domain adaptation

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 81bb667d-bcc1-49f8-9320-b0e111ae7781 · outbound

This paper cites Decoupled adaptation for cross-domain object detec- tion.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Decoupled adaptation for cross-domain object detec- tion

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.444747Z

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=2026-08-06T22:43:40.836376Z digest=sha256:bb2bf3162045960606da05ef432ad04cfe6fdb259830dc549d04891fa371c828

Observation e15da447-4c85-4cc2-a416-742e83e4d9ad · outbound

This paper cites Cat: Exploiting inter-class dynamics for domain adaptive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Cat: Exploiting inter-class dynamics for domain adaptive object detection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.435827Z

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=2026-08-06T22:43:40.936934Z digest=sha256:d9a3ec62a36026915bbc88a53e303a9ccfb9d872570c3b1b9141aad00d159623

Observation 53d4cc28-2bf7-47f6-acde-27932b563eb9 · outbound

This paper cites Object-aware domain generalization for object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Object-aware domain generalization for object detection

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.427439Z

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=2026-08-06T22:43:41.043056Z digest=sha256:84adb6de59a7b60c6cfeb49b34d686c7818a1fe88f86d54eb4091e9f72471516

Observation ef215e82-cf2e-4269-9da4-81d2e802763d · outbound

This paper cites Prompt-driven dynamic object-centric learning for single do- main generalization.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Prompt-driven dynamic object-centric learning for single do- main generalization

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.418784Z

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=2026-08-06T22:43:41.161377Z digest=sha256:15fa91dfb5d09eb4fe59e809794de34e7bd923d776214eab782276d82c19f3c1

Observation ed65c3f9-8b35-4bdf-a538-18af610d8685 · outbound

This paper cites Domain generalization with adversarial feature learning.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Domain generalization with adversarial feature learning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.410202Z

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=2026-08-06T22:43:41.264072Z digest=sha256:fba3509c09a16e17d5518b4c72a1e36baa211867d720440cf30e625549b2176d

Observation 8a505dfd-e72c-4e99-8f86-1772aae8d770 · outbound

This paper cites Grounded language-image pre-training.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Grounded language-image pre-training

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.401530Z

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=2026-08-06T22:43:41.399004Z digest=sha256:92af5a7a6024011517da35d22f2c1e63d881944bbd29044a2aad9c25f74a82ed

Observation fd38a3d6-6ede-44ec-a339-e8c4bf30b5a2 · outbound

This paper cites Source-free object detection by learning to overlook domain style.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Source-free object detection by learning to overlook domain style

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.392100Z

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=2026-08-06T22:43:41.465135Z digest=sha256:0c863a6538a7d8676a2c3020f2ee94c9aff38171f4c483d512b04ffdb00ce9a5

Observation f71a8a09-6e02-4a11-b3d3-a91893656d1a · outbound

This paper cites Sigma: Semantic- complete graph matching for domain adaptive object detec- tion.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Sigma: Semantic- complete graph matching for domain adaptive object detec- tion

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.382862Z

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=2026-08-06T22:43:41.544524Z digest=sha256:42bf4ca9f75a381e01831e232c4f3762ad7ca9238925bc4bb48d6857f2103802

Observation f5eff10c-62f8-40ed-8c2c-e746054b23e2 · outbound

This paper cites Sigma++: Im- proved semantic-complete graph matching for domain adap- tive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Sigma++: Im- proved semantic-complete graph matching for domain adap- tive object detection

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.373637Z

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=2026-08-06T22:43:41.605410Z digest=sha256:f1d86e3069f025d9222cf60370eabf2d7a2fb1e50dc11abb5b28cc966aa77ba5

Observation 66f68ea6-2cbc-45a4-95d4-de1ddd1f018f · outbound

This paper cites Cross-domain adaptive teacher for object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Cross-domain adaptive teacher for object detection

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.364574Z

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=2026-08-06T22:43:41.665238Z digest=sha256:be7a3e4ca82fedeccb3f68d41726d7150558e2cc58292ff8297b43141ff723cc

Observation bd2bdb71-c2e9-4d69-bc0b-53c3f39637cb · outbound

This paper cites Domain-invariant disentan- gled network for generalizable object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Domain-invariant disentan- gled network for generalizable object detection

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.354539Z

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=2026-08-06T22:43:41.705109Z digest=sha256:b0cad4239f09cd1ad8fd968ba2b83bdbb29ea1eafb9f0951686f56eb7ebe8bec

Observation 9454c2d8-ccbc-43f2-9f21-b0c35433214c · outbound

This paper cites Microsoft coco: Common objects in context.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Microsoft coco: Common objects in context

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.345227Z

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=2026-08-06T22:43:41.761588Z digest=sha256:2c09fbc1e05a69fad46d18fac43e69b29d69dce6827439cbc6306c27e7c8e6a9

Observation 7ac37cd2-d734-4ff4-8197-6ba5feec4078 · outbound

This paper cites Cigar: Cross-modality graph reasoning for domain adaptive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Cigar: Cross-modality graph reasoning for domain adaptive object detection

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.334672Z

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=2026-08-06T22:43:41.764249Z digest=sha256:2ab3cf5c54c9c42bed7d01817de3c597bc853d7bf842333931ceecc695feb95b

Observation e1b2c581-ac86-4480-92bb-4092b7527dd4 · outbound

This paper cites Unbiased faster r-cnn for single- source domain generalized object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Unbiased faster r-cnn for single- source domain generalized object detection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.324322Z

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=2026-08-06T22:43:41.768744Z digest=sha256:8c62245012b6aac8cead7c433e248d5c247959368d74ccd84b7985b379f24bc4

Observation 71e96280-0230-4eff-bcda-2004f0e2fc49 · outbound

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

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Swin transformer: Hierarchical vision transformer using shifted windows

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.315409Z

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=2026-08-06T22:43:41.781193Z digest=sha256:a7bab467940eb877b58b305f6b61cd252fa9a3afddb6c9ecdbff9ac19e91d253

Observation 3eef6879-1c5d-43a1-96da-ae26456c0cf7 · outbound

This paper cites A convnet for the 2020s.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability A convnet for the 2020s

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.784827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.784827Z digest=sha256:0d7aa2b03fef46e32b7d4d70940e21d8e70a0cc49bccdd371a6c1532ef809b3e

Observation 96d9731c-5e98-4a58-bbab-0f4d369ed25b · outbound

This paper cites Diffusion hyperfeatures: Searching through time and space for semantic correspondence.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Diffusion hyperfeatures: Searching through time and space for semantic correspondence

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.300848Z

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=2026-08-06T22:43:41.788535Z digest=sha256:cb91f444e3a0f94c36d5a93d3c00f77e26b32b246d127c3d2dca99c8815b1420

Observation 94579aac-f4a2-4c5f-b28c-30cb630682b7 · outbound

This paper cites Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.792002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.792002Z digest=sha256:c795016c6618046ff79caf1b34ae4e3c062e7fe87bab95c78df29e6aff18d099

Observation fc03da3d-9916-4c9a-a867-8f5a57238f0a · outbound

This paper cites Zero-shot text-to-image generation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Zero-shot text-to-image generation

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.795474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.795474Z digest=sha256:1ae343dc44fb054d17d87d6fc74c9991970021497413ab3f19b8af7c3a6792dc

Observation 11585516-c823-4263-9d44-79ca8774932a · outbound

This paper cites Srcd: Semantic reasoning with com- pound domains for single-domain generalized object detec- tion.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Srcd: Semantic reasoning with com- pound domains for single-domain generalized object detec- tion

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.286536Z

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=2026-08-06T22:43:41.799343Z digest=sha256:9ce2bc4852598b917893564fee21dba5a77f562a1404e38cbdf90f31a4173318

Observation 8b16d8ca-2b7a-4176-aaa5-3af95c42db3a · outbound

This paper cites YOLOv3: An Incremental Improvement.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability YOLOv3: An Incremental Improvement

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.802526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.802526Z digest=sha256:3b6cb15cfdebde22b0ae7194e6e517f5b580fac384cf99345cee4b277fd8ea69

Observation 808eb2ac-f3d8-4d5a-ae50-5fd78977d5b2 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.276920Z

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=2026-08-06T22:43:41.806677Z digest=sha256:f65165ab729c0aff8b691dc62681b4c54c580f91866a97880ebd9816ea9b44ce

Observation bc3f5ed5-95ea-4eac-b7b2-4c3b9e4ab716 · outbound

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

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability High-resolution image synthesis with latent diffusion models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.809838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.809838Z digest=sha256:ea7c9b9eee50e674ec24f03e2aa9be37cd63a631046854649cb2dc15a36f40b7

Observation 12b0350c-9201-4d35-ad8c-cb4929d53db0 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Photorealistic text-to-image diffusion models with deep language understanding

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.812912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.812912Z digest=sha256:ca0f5f8637bcd6501ab6f0cd7668a4423d48c84794e1f3ea08787672e28b3b39

Observation af803935-eb30-432c-9987-3f5533dc89e9 · outbound

This paper cites Strong-weak distribution alignment for adaptive ob- ject detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Strong-weak distribution alignment for adaptive ob- ject detection

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.256019Z

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=2026-08-06T22:43:41.816093Z digest=sha256:1cd6e46bd8a7c27efc4e706b36fed0dcb58e77edbedc74f64e5f25032d3939e9

Observation fbe6bc3a-fb1f-4128-bc83-c4f05c621ae3 · outbound

This paper cites Seman- tic foggy scene understanding with synthetic data.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Seman- tic foggy scene understanding with synthetic data

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.246578Z

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=2026-08-06T22:43:41.819465Z digest=sha256:773ee03801833bfbdba8f5e773936556f42d64b2973c28b95e99b99ca92acd14

Observation d6e2536d-9d54-400e-a684-732830d802f2 · outbound

This paper cites Denoising Diffusion Implicit Models.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Denoising Diffusion Implicit Models

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T22:43:41.822590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.822590Z digest=sha256:62cd2e039d6c5edee2954a51cf4e8e77f37f0237587c5426b00024ecdf3b496e

Observation d3a47591-fc5f-47a7-8662-f63f5bd7a38d · outbound

This paper cites Fsce: Few-shot object detection via contrastive pro- posal encoding.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Fsce: Few-shot object detection via contrastive pro- posal encoding

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.236785Z

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=2026-08-06T22:43:41.826978Z digest=sha256:ea448aa3ada9bd5170ba016a23bc2f6f19f066f8c3087b96e4042f7212c99e55

Observation 25e9a2db-b69d-41a5-b0fc-ac74b2f7647e · outbound

This paper cites Emergent correspondence from image diffusion.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Emergent correspondence from image diffusion

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.227936Z

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=2026-08-06T22:43:41.830131Z digest=sha256:9938c8589403f948a1b9b720773abf28c7e0e62f2b54aeaf20c66d7020ec85f5

Observation fbc7f723-63da-449d-9446-709244463ae0 · outbound

This paper cites Fcos: A simple and strong anchor-free object detector.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Fcos: A simple and strong anchor-free object detector

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.218179Z

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=2026-08-06T22:43:41.833292Z digest=sha256:30844d16518749380c3d2a45544934927c06e5a65bb0698d0822d3d7f9bec61d

Observation fe095c62-7f75-4e42-bfb1-ab29b5ca1d30 · outbound

This paper cites Clip the gap: A single domain generalization approach for object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Clip the gap: A single domain generalization approach for object detection

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.209253Z

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=2026-08-06T22:43:41.836571Z digest=sha256:cdb1e2be506a4bf81fee3a9b40e374d66e7e4fa82b31a35010eb1d4449e68506

Observation 1baa45c1-3e2d-419d-ae20-cdd7086abbeb · outbound

This paper cites Generalizing to unseen domains: A survey on do- main generalization.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Generalizing to unseen domains: A survey on do- main generalization

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.200071Z

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=2026-08-06T22:43:41.839611Z digest=sha256:5a6adf4b2ee77c83d0d4c481835e91f586b36b8efa5eab437a3ca41fab009821

Observation 8fb3d7a0-dedc-461b-a5d8-49cd5e0cff38 · outbound

This paper cites Crosskd: Cross-head knowledge distillation for object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Crosskd: Cross-head knowledge distillation for object detection

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.190575Z

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=2026-08-06T22:43:41.842763Z digest=sha256:85b2828ffb2be7a3dc6dde3a9023091ba2aa3d54da3993d81f729bf245eb0a2f

Observation f644bd35-dd96-461b-a526-f41f9b7cd618 · outbound

This paper cites Instancediffusion: Instance- level control for image generation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Instancediffusion: Instance- level control for image generation

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.181009Z

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=2026-08-06T22:43:41.846196Z digest=sha256:ece3fd8493a105cba571c5b4e6eee7c32ba210bf57d012353631afa5626917a2

Observation 705ace2e-9940-47da-b635-f264b654f836 · outbound

This paper cites Detdiffusion: Synergizing gen- erative and perceptive models for enhanced data generation and perception.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Detdiffusion: Synergizing gen- erative and perceptive models for enhanced data generation and perception

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.171703Z

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 6d471c33-0e4b-4de0-83c5-dad87d3fbc75 · outbound

This paper cites Mean teacher detr with masked feature alignment: a robust domain adaptive detection trans- former framework.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Mean teacher detr with masked feature alignment: a robust domain adaptive detection trans- former framework

Reference 70

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

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Observation 305454ec-ecc0-4885-aead-42665f67ae4c · outbound

This paper cites Single-domain generalized ob- ject detection in urban scene via cyclic-disentangled self- distillation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Single-domain generalized ob- ject detection in urban scene via cyclic-disentangled self- distillation

Reference 71

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no resolver link, observed 2026-08-06T22:43:41.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.855783Z digest=sha256:5e187818455ba3518297476bb96673487a94c0e2eb15a8f83dfa6a18b67a9490

Observation e2ad4ea3-a25e-410a-bfa0-234567c31664 · outbound

This paper cites G-nas: Generalizable neu- ral architecture search for single domain generalization ob- ject detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability G-nas: Generalizable neu- ral architecture search for single domain generalization ob- ject detection

Reference 72

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verified fuzzy
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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 fd14e8ea-6a68-4c8d-88b3-eee620a93bc0 · outbound

This paper cites Exploring categorical regularization for domain adap- tive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Exploring categorical regularization for domain adap- tive object detection

Reference 73

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verified fuzzy
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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=2026-08-06T22:43:41.862188Z digest=sha256:e604ec826919a0a09584e789e5a7f7127d71730cc48c9c7b81468a1ae6dc85fb

Observation d6a2863a-c659-4e09-af60-06be7120f89f · outbound

This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 74

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.866068Z digest=sha256:8b97615a2b884bdd201ac4bcdb3ac79fae15199ab0ff09834fc5d7b876f116f6

Observation 9dd9ef82-5127-4be2-a137-a95ac6c607ec · outbound

This paper cites Multi-view adversarial discriminator: Mine the non-causal factors for object detection in unseen domains.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Multi-view adversarial discriminator: Mine the non-causal factors for object detection in unseen domains

Reference 75

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verified fuzzy
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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=2026-08-06T22:43:41.869033Z digest=sha256:4ced2adfc1da05af106994242a7493f1dae4cf3523ae99f4a1de4863a3901e21

Observation e24bda34-5716-4949-bf1b-8cbe5f4a327a · outbound

This paper cites A fourier-based framework for domain generaliza- tion.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability A fourier-based framework for domain generaliza- tion

Reference 76

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verified fuzzy
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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=2026-08-06T22:43:41.872402Z digest=sha256:6e13f6d0404ab0879314c6e0c55dfea0c459504ae633c45fa7738c793adc409e

Observation bfc38c7d-9a43-48a5-8b15-ed94f84a9038 · outbound

This paper cites PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection

Reference 77

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.875843Z digest=sha256:b8ad8595daaadb3884c2c9150683052652b25602c551eccd6a61c49b8a16830a

Observation cf458bbc-54aa-45fd-a5b9-de442cae1fb7 · outbound

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

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Fda: Fourier domain adaptation for semantic segmentation

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.104045Z

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=2026-08-06T22:43:41.879252Z digest=sha256:46df3e4f001a1b7b5390077cf708d01d53179ade91de9c4f12f0dc1a5f667e87

Observation d7ae33fd-6eb3-43d0-928c-bad6a82c52a6 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 79

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.882487Z digest=sha256:3e40695ae4d86217ec00bae312620814b7621a2119b6bcd8a77ada162c9c2a51

Observation ba3bafc5-3402-461c-8253-08631f31df86 · outbound

This paper cites Mttrans: Cross- domain object detection with mean teacher transformer.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Mttrans: Cross- domain object detection with mean teacher transformer

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.089435Z

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=2026-08-06T22:43:41.885174Z digest=sha256:366e383e2896e66be783e3f35e3c7b2ea0f260fc90dc89a1414d6d7de7c54cf5

Observation 094cc018-3989-4cda-8a34-01e13b8269d3 · outbound

This paper cites Dino: Detr with improved denoising anchor boxes for end-to-end object de- tection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Dino: Detr with improved denoising anchor boxes for end-to-end object de- tection

Reference 81

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verified fuzzy
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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=2026-08-06T22:43:41.888161Z digest=sha256:6d76a132fee25d761e6e0810fd80f6c9cafde05fda24f4313c1c7027bce13fc4

Observation 8709e612-28e7-4325-867b-4126fb5fde26 · outbound

This paper cites Robust domain adaptive object detection with unified multi-granularity alignment.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Robust domain adaptive object detection with unified multi-granularity alignment

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.070528Z

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=2026-08-06T22:43:41.891598Z digest=sha256:5b0629b459c4e46e26871e586e521e922746d2862ad64727f83ecbc992d540fc

Observation cd46b564-ae5d-42ad-8a31-1b0b36ddc481 · outbound

This paper cites Task-specific inconsistency alignment for domain adaptive object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Task-specific inconsistency alignment for domain adaptive object detection

Reference 83

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verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.061163Z

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=2026-08-06T22:43:41.894673Z digest=sha256:3e0ecd889107d000c167f3af543629de84f7d1ffdbafaaa0b254a19b02112840

Observation d815f8d9-28ba-42c2-b462-1dfbda44c0b0 · outbound

This paper cites Style-hallucinated dual consistency learning for domain generalized semantic segmentation.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Style-hallucinated dual consistency learning for domain generalized semantic segmentation

Reference 84

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verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.051314Z

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=2026-08-06T22:43:41.897723Z digest=sha256:47747e6e2ef8b486dff85924fe564e886f326d20663e71e10055595e70735797

Observation d4e54b25-a4c5-4725-bae4-04f3666261fa · outbound

This paper cites Domain Generalization with MixStyle.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Domain Generalization with MixStyle

Reference 85

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no resolver link, observed 2026-08-06T22:43:41.901338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.901338Z digest=sha256:47228de9b68b97b9a7b4efd910891478713d38a915c4048724f3cd0d1261fcb0

Observation 6619046c-5b61-4a81-bb75-d332fe687baa · outbound

This paper cites Domain generalization: A survey.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Domain generalization: A survey

Reference 86

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unresolved
no resolver link, observed 2026-08-06T22:43:41.904870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.904870Z digest=sha256:b7f9254ae6d5b4ea835f3de3047b675df6bb26eead3b7fcc939bcdf19deddf02

Observation 331a6b96-3551-4d76-91b5-2dd4415fc625 · outbound

This paper cites Multi-granularity alignment domain adaptation for object detection.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Multi-granularity alignment domain adaptation for object detection

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.035857Z

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=2026-08-06T22:43:41.907870Z digest=sha256:641823d5856e272d232a486936f5098789ec7feb887216bf739040faee455b34

Observation 721fb3e8-8d33-453f-83e8-b3d1381f9b1e · outbound

This paper cites Unsupervised domain adaptive detection with network sta- bility analysis.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Unsupervised domain adaptive detection with network sta- bility analysis

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.025464Z

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=2026-08-06T22:43:41.911010Z digest=sha256:2644a32fca380dd20fd3e50d7fe7f43451aca704afca14829edab16963c09b4e

Observation cf441112-0ca0-4328-9ae8-7aa41950419c · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 89

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unresolved
no resolver link, observed 2026-08-06T22:43:41.914525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:43:41.914525Z digest=sha256:e5117667e91a93a774244048bea94968fa63267be4eed6012b774c87830db3bd

Observation f9bc0164-a01c-4191-9c7a-d1477b58f517 · outbound

This paper cites Localized adversarial domain generalization.

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability Localized adversarial domain generalization

Reference 90

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verified fuzzy
raw_fallback, observed 2026-08-06T22:43:42.009995Z

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=2026-08-06T22:43:41.918011Z digest=sha256:0ed2244260ac03abc85584582864ecebf421de826e67d7549c51d411875f4570

Pith citing papers

Observation d72c5ece-6780-4cb8-aafd-801e303e76ba · inbound

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance cites this paper.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability

Reference 67

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verified exact
local_arxiv, observed 2026-08-09T00:37:40.400254Z

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=2026-08-09T00:37:40.360050Z digest=sha256:6a2adc2bf0eca9bb00460eb22a51afc2a2844713c48fa21193855b8b55358670