Paper Citation Record · LEDGER

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance

As of 9 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 2 inbound Pith citation observations for arXiv:2502.03835.

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

pith.paper-citation-record.v1
2502.03835 v2

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:37:40.369484Z

measured 73 of 73 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:43:40.014919Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:51:24.780237Z

Reference resolution

71 of 71 outbound references displayed

verified exact4
verified fuzzy54
unresolved13
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aec24069-9d6d-4740-8f16-0617bdae5d8c · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.182908Z

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Observation a8d7a1e8-c77a-410d-84ad-f260f96bb8ec · outbound

This paper cites FCOS: Fully Convolutional One-Stage Object Detection.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance FCOS: Fully Convolutional One-Stage Object Detection

Reference 2

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Observation 637853f0-3e2f-4fd2-a0cd-e342603837d1 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance YOLOX: Exceeding YOLO Series in 2021

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.168426Z

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Observation f65155cb-56d9-4236-afb9-1b5e88d2dcc2 · outbound

This paper cites Generalized and discriminative few-shot object detection via svd-dictionary enhancement,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Generalized and discriminative few-shot object detection via svd-dictionary enhancement,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.173594Z

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Observation 5d8abc40-74fc-4bef-82ce-d6d450c104b9 · outbound

This paper cites Harmonizing transferability and discriminability for adapting object detectors,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Harmonizing transferability and discriminability for adapting object detectors,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.164855Z

Source-reported events for the cited work

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Observation 6f49a74e-c42f-4bc4-b918-8823086f824c · outbound

This paper cites Unbiased look at dataset bias,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Unbiased look at dataset bias,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.155996Z

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.

Observation 50c33de3-72a6-4bc8-a883-7b18544bcd96 · outbound

This paper cites Generalizing to unseen domains: A survey on domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Generalizing to unseen domains: A survey on domain generalization,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.186643Z

Source-reported events for the cited work

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Observation 582a7f48-1a67-47e4-a305-3b17e500757c · outbound

This paper cites A theory of learning from different domains,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance A theory of learning from different domains,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.189460Z

Source-reported events for the cited work

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Observation 858544f8-b629-4d78-9aae-1204039cc171 · outbound

This paper cites Domain-adversarial training of neural networks,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Domain-adversarial training of neural networks,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.192277Z

Source-reported events for the cited work

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Observation 416d2e25-dd8a-4fe8-9745-75aecfbb1d4a · outbound

This paper cites Optimal transport for domain adaptation,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Optimal transport for domain adaptation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.123976Z

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.

Observation eb82e2b9-adf9-4009-97b6-4a37de3634f5 · outbound

This paper cites Domain invariant representation learning with domain density transformations,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Domain invariant representation learning with domain density transformations,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.115343Z

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.

Observation 1c27cba3-f009-4206-aa2f-59301ede59f3 · outbound

This paper cites Gradient-aware domain-invariant learning for domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Gradient-aware domain-invariant learning for domain generalization,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.106724Z

Source-reported events for the cited work

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Observation aaa413bf-3303-45a0-87b3-4894a7c472b6 · outbound

This paper cites Do- main generalization via model-agnostic learning of semantic features,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Do- main generalization via model-agnostic learning of semantic features,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.097821Z

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.

Observation 320fce6e-8b54-4e9b-a6cf-3172ed241aa8 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Unbiased faster r-cnn for single-source domain generalized object detection,

Reference 14

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Observation 2f24724e-5992-4ca9-bb6d-800f855f2b92 · outbound

This paper cites Prompt-driven dynamic object- centric learning for single domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Prompt-driven dynamic object- centric learning for single domain generalization,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.084453Z

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.

Observation c77866a7-e521-482b-9274-70218a5a5288 · outbound

This paper cites G-nas: Generalizable neural architecture search for single domain generalization object detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance G-nas: Generalizable neural architecture search for single domain generalization object detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.075440Z

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.

Observation 43ca3f6b-6f74-4282-8351-4fe83063b251 · outbound

This paper cites Domain general- ization: A survey,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Domain general- ization: A survey,

Reference 17

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Source-reported events for the cited work

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Observation cdb83498-3b6a-4609-aa08-1c75fd3ba4d9 · outbound

This paper cites Wildnet: Learning domain generalized semantic segmentation from the wild,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Wildnet: Learning domain generalized semantic segmentation from the wild,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.060609Z

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.

Observation 1f31a846-891a-4275-acb3-3b925bce6534 · outbound

This paper cites Deep discriminative causal domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Deep discriminative causal domain generalization,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.051602Z

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.

Observation ea98b997-0a33-40f8-95b2-101cacc80df9 · outbound

This paper cites Frustratingly Simple Domain Generalization via Image Stylization.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Frustratingly Simple Domain Generalization via Image Stylization

Reference 20

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Observation 26350761-74d5-4436-a7d7-6d9f36dedc9a · outbound

This paper cites Learning to diversify for single domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Learning to diversify for single domain generalization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.042820Z

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.

Observation 5c6d8ffd-7499-4232-9841-cdf4fd8003d5 · outbound

This paper cites Multi-adversarial discriminative deep domain generalization for face presentation attack detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Multi-adversarial discriminative deep domain generalization for face presentation attack detection,

Reference 22

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Observation 40284a97-49a0-42f8-854c-eb2f3ac17ed4 · outbound

This paper cites Meta-causal learning for single domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Meta-causal learning for single domain generalization,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.029344Z

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.

Observation 54c350d3-0ac6-4876-9b7d-d7307807f3ca · outbound

This paper cites Learning to learn with variational information bottleneck for domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Learning to learn with variational information bottleneck for domain generalization,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.021343Z

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.

Observation 852debc2-6bd4-4c75-871b-7db30f61b820 · outbound

This paper cites Semantic-aware domain generalized segmentation,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Semantic-aware domain generalized segmentation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.012926Z

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.

Observation 1d85757d-5be8-47d4-a0ee-9ff6b59d3dd5 · outbound

This paper cites Learning to optimize domain specific normalization for domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Learning to optimize domain specific normalization for domain generalization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.004425Z

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.

Observation baaae18e-fbd8-4e60-89ce-820785aadf9f · outbound

This paper cites Improving generalization of meta-learning with inverted regularization at inner- level,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Improving generalization of meta-learning with inverted regularization at inner- level,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.995744Z

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.

Observation 3903340f-0efc-4657-9568-387d54dc1bf9 · outbound

This paper cites Learning to generalize unseen domains via memory-based multi-source meta- learning for person re-identification,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Learning to generalize unseen domains via memory-based multi-source meta- learning for person re-identification,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.987423Z

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.

Observation 8e913b99-90f4-42f2-bb1b-afa4577c4dc1 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance I3net: Implicit instance-invariant network for adapting one-stage object detectors,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.979266Z

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.

Observation c0c9324a-a194-4bde-97d6-7d45291be855 · outbound

This paper cites Unbiased mean teacher for cross- domain object detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Unbiased mean teacher for cross- domain object detection,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.971132Z

Source-reported events for the cited work

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Observation 016ae9c7-3fff-4bd3-88e0-4b94705de483 · outbound

This paper cites MILA: Memory-Based Instance-Level Adaptation for Cross-Domain Object Detection.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance MILA: Memory-Based Instance-Level Adaptation for Cross-Domain Object Detection

Reference 31

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Observation 523162d4-4c4a-4470-ab9e-4908b5ca81ea · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Cross-domain adaptive teacher for object detection,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.963041Z

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

Observation 06fec211-73dd-459e-abde-f625561c488e · outbound

This paper cites Unsupervised domain adaptation of object detectors: A survey,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Unsupervised domain adaptation of object detectors: A survey,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.955007Z

Source-reported events for the cited work

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Observation d8933ec4-92e7-4fd2-8238-b4f2152b47bd · outbound

This paper cites A review of single-source deep unsupervised visual domain adaptation,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance A review of single-source deep unsupervised visual domain adaptation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.946411Z

Source-reported events for the cited work

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Observation abac1801-5df0-48c6-adb1-b1dd725f43cf · outbound

This paper cites Contrastive mean teacher for domain adaptive object detectors,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Contrastive mean teacher for domain adaptive object detectors,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.938059Z

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Observation f663d0bb-b69d-4bc5-8675-b79dff09eac8 · outbound

This paper cites Strong-weak distri- bution alignment for adaptive object detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Strong-weak distri- bution alignment for adaptive object detection,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.929623Z

Source-reported events for the cited work

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Observation 66cde873-aca5-4ef6-b107-b98674611083 · outbound

This paper cites Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection

Reference 37

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Observation cdff2af8-3b21-4770-bbd5-9ba7bc838f65 · outbound

This paper cites Towards generalizable multi-object tracking,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Towards generalizable multi-object tracking,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.920774Z

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.

Observation 6e54050a-57dd-4cf8-b614-f6e4a102cc9a · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Clip the gap: A single domain generalization approach for object detection,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.912231Z

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.

Observation 0445e13f-fa4a-4701-9c1d-33528de25a70 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Improving single domain-generalized object detection: A focus on diversification and alignment,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.903446Z

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.

Observation 6d079793-2447-4523-86a6-1a4d6faa9979 · outbound

This paper cites Object-aware domain gen- eralization for object detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Object-aware domain gen- eralization for object detection,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.893871Z

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.

Observation 9e35fe72-ce95-404a-ac0f-fc8e0af8e8db · outbound

This paper cites Two at once: Enhancing learning and generalization capacities via ibn-net,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Two at once: Enhancing learning and generalization capacities via ibn-net,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.885820Z

Source-reported events for the cited work

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Observation 40176ce1-9ef1-48c2-9726-71e3cead2ab6 · outbound

This paper cites Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.877173Z

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.

Observation ce703cf1-febe-432e-93cc-0c84fed879ef · outbound

This paper cites Iterative normalization: Beyond standardization towards efficient whitening,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Iterative normalization: Beyond standardization towards efficient whitening,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.868393Z

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.

Observation f29ddbbc-adc6-4595-a46c-63e74c4869af · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Single-domain generalized object detection in urban scene via cyclic-disentangled self-distillation,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.859721Z

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.

Observation 82bb4ee7-0e38-40cd-83e7-4c0a88e51c66 · outbound

This paper cites Adversar- ial target-invariant representation learning for domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Adversar- ial target-invariant representation learning for domain generalization,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.850799Z

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.

Observation 10a4d04f-88cd-4cf1-97e0-5276ef7bb212 · outbound

This paper cites Order-preserving consistency regularization for domain adaptation and generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Order-preserving consistency regularization for domain adaptation and generalization,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.841686Z

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.

Observation 1e79963f-3570-4cac-af12-e112a123ee03 · outbound

This paper cites Switchable whitening for deep representation learning,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Switchable whitening for deep representation learning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.831627Z

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.

Observation 8cecab13-c19c-4182-8ec4-317ede082634 · outbound

This paper cites Style-hallucinated dual consistency learning for domain generalized semantic segmenta- tion,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Style-hallucinated dual consistency learning for domain generalized semantic segmenta- tion,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.823032Z

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.

Observation e543bac1-02e0-496d-ae19-ec33161e84fe · outbound

This paper cites Srcd: Se- mantic reasoning with compound domains for single-domain generalized object detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Srcd: Se- mantic reasoning with compound domains for single-domain generalized object detection,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.814517Z

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.

Observation 0ece4e1e-e68d-4100-9254-0caf9bb8eb21 · outbound

This paper cites Sdg-yolov8: Single-domain generalized object detection based on domain diversity in traffic road scenes,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Sdg-yolov8: Single-domain generalized object detection based on domain diversity in traffic road scenes,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.805322Z

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

Observation 9e2f43d7-b0c6-46ef-8eef-f45b64a0c208 · outbound

This paper cites Let synthetic data shine: Domain reassembly and soft-fusion for single domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Let synthetic data shine: Domain reassembly and soft-fusion for single domain generalization,

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-08-09T00:37:40.609542Z

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Observation 6b52753e-44f2-4331-9ab8-99b593e79aa8 · outbound

This paper cites An enhanced domain generalization method for object detection based on text guided feature disentangle- ment,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance An enhanced domain generalization method for object detection based on text guided feature disentangle- ment,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.796179Z

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

Observation b3090669-d6b0-4eb6-9618-d4564b27ff25 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Imagenet: A large-scale hierarchical image database,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.321414Z

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Observation 5e876ac7-0996-406f-843a-2a164b23e21c · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Bdd100k: A diverse driving dataset for heterogeneous multitask learning,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.324234Z

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Observation 06bc2ee8-d8c7-48d9-a554-2a38b95afffa · outbound

This paper cites Vehicle detection and tracking in adverse weather using a deep learning frame- work,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Vehicle detection and tracking in adverse weather using a deep learning frame- work,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.776921Z

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

Observation ade36c1b-bd03-416c-bdb2-96c50f8a0218 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance The cityscapes dataset for semantic urban scene understanding,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.329571Z

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Observation ad15cee9-49ab-4b40-b973-d575e5428e94 · outbound

This paper cites Vector-decomposed disentanglement for domain-invariant object detection,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Vector-decomposed disentanglement for domain-invariant object detection,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.763133Z

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

Observation 6ffc7de6-c42d-4419-ae57-9d7b291972da · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance The pascal visual object classes (voc) challenge,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-09T00:37:40.335187Z

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Observation 6abe599e-c6b0-466b-ba4c-17654e6de986 · outbound

This paper cites Cross-domain weakly-supervised object detection through progressive domain adap- tation,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Cross-domain weakly-supervised object detection through progressive domain adap- tation,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.749301Z

Source-reported events for the cited work

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Observation 9914a368-c905-4955-ac93-bd07f14f17c5 · outbound

This paper cites Semantic foggy scene under- standing with synthetic data,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Semantic foggy scene under- standing with synthetic data,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.740729Z

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.

Observation 2e455a83-2769-4ac4-8101-657f86dfb7a7 · outbound

This paper cites Depth-attentional features for single-image rain removal,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Depth-attentional features for single-image rain removal,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.732402Z

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.

Observation 59048421-a50c-4a09-b04f-ddd363ba0881 · outbound

This paper cites Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.723237Z

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.

Observation b43076a0-9d0a-4c31-a8f4-0e51cea3c302 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Dual bipartite graph learning: A general approach for domain adaptive object detection,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.714465Z

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.

Observation dac21b55-de22-4df4-9aa6-1bbce45e894c · outbound

This paper cites Towards robust object detection invariant to real-world domain shifts,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Towards robust object detection invariant to real-world domain shifts,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.704658Z

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.

Observation c502661c-270e-4b30-9676-e9e0933e1f47 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Generalized diffusion detector: Mining robust features from diffusion models for domain- generalized detection,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.695374Z

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.

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

This paper cites Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability.

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

Resolution: 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.

Observation 485b31e3-1230-4a1b-9ff4-d1aa51a995f5 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance A fourier-based framework for domain generalization,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.686310Z

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.

Observation 7f0b3b31-4178-410b-a797-d469de65969c · outbound

This paper cites Frequency space domain randomization for domain generalization,.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Frequency space domain randomization for domain generalization,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.676742Z

Source-reported events for the cited work

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Observation 96e44972-7c15-482e-9b52-5044df129e78 · outbound

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

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance Multi-view adversarial discriminator: Mine the non-causal factors for object detection in unseen domains,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:40.667584Z

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Observation ea2bfb62-a348-4f78-8385-3df3d7b67ea8 · outbound

This paper cites 1521–1528.

Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance 1521–1528

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:37:41.147421Z

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.

Pith citing papers

Observation bf91c686-6074-4f89-9640-fe18826b8fe9 · inbound

Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability cites this paper.

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

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:40.014919Z

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Observation 8e478b9c-5338-4786-994e-a82b99766cf5 · inbound

Bridge: Basis-Driven Causal Inference Marries VFMs for Domain Generalization cites this paper.

Bridge: Basis-Driven Causal Inference Marries VFMs for Domain Generalization Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:51:24.783028Z

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