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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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
  • metadata mismatch0

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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Unavailable: canonical work link unavailable.

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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

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raw_fallback, observed 2026-08-09T00:37:41.173594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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

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raw_fallback, observed 2026-08-09T00:37:41.164855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.176170Z digest=sha256:1244aba8d3aa092b57dd8016bc149de0cbc887bdbdefa10a0b8adbfccda828ce

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.186643Z digest=sha256:b76e05c11d8a555f8ca810630dd212dae11f60a5e95fdf33991f9ebcf8985ca3

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.192277Z digest=sha256:3b04e9efb495c8ce763077d199df80cd76f6760a61612406f0a8cfc80a48eafd

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.195033Z digest=sha256:92ed6e31590a8edad62ba73402f148a0f26c9b232c9ddc5ab40a1d6044cd2daf

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.198104Z digest=sha256:8a13afde86bd8bdfe9507707267f9a485000b92616d9ad0434acc1d9d641f4cf

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

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raw_fallback, observed 2026-08-09T00:37:41.106724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.204129Z digest=sha256:026f43d8e99332a35c725bef1b6f89a237785629cb99ca99644f0addd8c587b3

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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unresolved
no resolver link, observed 2026-08-09T00:37:40.206991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.206991Z digest=sha256:52977df2deaac9f69684b95fc0d9b10cbea7cacb8ef5366aaf9aa6451634a414

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.209870Z digest=sha256:cc8a21c35f3f96295aead670f6bcbbee5dad7b18f22e3979dfeae861ed8270e5

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.212373Z digest=sha256:26f3a67bbcbcde97a7e6efddd75e12411e4dc21cdb2a6d7247ed01237e4629a7

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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no resolver link, observed 2026-08-09T00:37:40.215052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.217812Z digest=sha256:c9a09e4e4c27fd6a294593a06939f45aabe97dbad85791c173570b789e844c3e

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.220592Z digest=sha256:17f86cfe5902b4f03f67fb06fb1b9485d1b1d02c8a83c6f0efae6f49af888c80

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.223375Z digest=sha256:29b074ef6cc3e57cbd9adc1ea0aca8bc0a5ba6ed1cc9f406b23a384c7198bac9

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.226799Z digest=sha256:aa93bde9fd44a9227e4990cf2eeaa0cdb3552eb2d49027ae756f69d2760a7eec

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.229596Z digest=sha256:47ec4265ac748a6b9c27378fe8caec0a9a12fe775e96a2330a554e13486ed18e

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

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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 2026-08-10T06:31:04.303077+00:00.

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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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.235176Z digest=sha256:b766aadaf6de407abd2755293280fc1f9a2e401ffc516e2eef0836cef955bf45

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.238508Z digest=sha256:a2b520de438351b5532eb4187efd2253f7630b00c4abcda0b7a1b808f0e3f678

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

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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 2026-08-10T06:31:04.303077+00:00.

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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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.245293Z digest=sha256:0d00852f7be548a2162dc6ecd6aea8b15986e0f12b41181760ed0cae5bdb1c6b

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.248056Z digest=sha256:9381012c9bb33a72003de86682a6aecde75b25ef72b272a05d4bc74cd03ad6e3

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.250851Z digest=sha256:dbf5d385b988c6b9d435dd3c95d0ca2e213d39c32f7f3c447fbb61eaa5f31f6f

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

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raw_fallback, observed 2026-08-09T00:37:40.971132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.253651Z digest=sha256:0a3378fb93df5e710735ad7dad9905016aa2670ebd4280d0a7e53b5b33251750

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

Resolution
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local_arxiv, observed 2026-08-09T00:37:40.634516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.256336Z digest=sha256:a2e1f1ed0b88d07a7d772f0ffa7d183e9d1cbb7f135312cd270b53f4133e5b2a

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

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raw_fallback, observed 2026-08-09T00:37:40.963041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.259400Z digest=sha256:7014d8c5ea18d5dd3b322779df8c3ff66026d33cec7f47c60bedd0dbf243ecf7

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

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raw_fallback, observed 2026-08-09T00:37:40.955007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.262130Z digest=sha256:ceb44657d3d15d5b60cada0321224112acd4958164630c91ce915cb1435888ce

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.264835Z digest=sha256:d5f9a4afad7f4e0fcb4ff3fd841d797bc22e3dfad6192e2d82962276946cc7a4

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.267865Z digest=sha256:b2c3444ece41f2a4025c6515e6ce9b1dbc8373543166e027804dcfcc90fdc71b

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.271024Z digest=sha256:02f393a648a071aeab9bfe11d0c9826c6c97fa59499389f7685447e14bdee315

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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verified exact
local_arxiv, observed 2026-08-09T00:37:40.622496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.273845Z digest=sha256:8116d52e23bd4b123e8ce9b1db14d09b2db27b038bcad1642c0feb80fdf74df9

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.276857Z digest=sha256:2afb8461041c51d3b806c2e02e57f6d950d0a3884f7a3c6c6d2c8641ecf27e8d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.279578Z digest=sha256:aae3c2edbee097f72956ffda6366a1d6b6e5a953cac367a1ac2de0e58f0d4274

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.282792Z digest=sha256:efc3fe41caf3599e6e545188cdb5232edfe22ab700ec40bb2845fe8bef205b29

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.286374Z digest=sha256:2caa00d31cb1c6dc1a9426e308db38fc3f94d80af8923bdd6aa050b0a5009d0c

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.289013Z digest=sha256:0c608f8d9fab6744a26b44cb829a392eb2f08f050e8f93a80066cc58e419dcaa

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.291823Z digest=sha256:ef4acb9b99681c294781ca1d355ac9ff52a99fbcc8b2e687fc0e4a065d61e2ad

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.294481Z digest=sha256:c3cb69dfa67ebcd7a2441b4be3515a5d1b99e55a874aef6089b3beede9e1c6ab

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.297216Z digest=sha256:371b5149e84b9be8e4cf8cf885c0d38a0087b5f3f5ea16fbdf843572c24e1c50

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.299759Z digest=sha256:475dc776fd0fe770c9ca46dac8fbd071fe4970d5e760500d1be39c5ddd05b9c0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.302408Z digest=sha256:eac40d6c6d0bdf52da9272560b0426d7f99663ab6606b519cf0fd430820ec652

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.305083Z digest=sha256:254e6a910a3c2dc5ae7b8d2d91d706fd40edef12334a8535c9fc614dfe67a8c1

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.307684Z digest=sha256:847c74a330aa2e78d9be5c2187633d7737b84a50fe124ce012a0f5cf0ae9cccc

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.310582Z digest=sha256:6c6863fe481d648ff84a67d35eb336454620ff48a151aa110aa9d56c5f8b66b2

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.313359Z digest=sha256:910038cdf0375535b213de36bafe9fe89b19fbba182f3b676a200e99bad52b53

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.315917Z digest=sha256:70fcf69dea2598a26c1115d659a0c97904e3db14576fe39690d1996be69074bd

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.318728Z digest=sha256:abe92fe26d648786afd037dd1c6aa86b50384ada300a6c68b411adc8bea50115

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.321414Z digest=sha256:8888f22b8ddfc5f89e195956118a56a8308d507c996e5f2d377284277034b624

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.324234Z digest=sha256:2ce733a12a874edcef956bcdb1905d9642420cda774d14b69b2a22446be3eda6

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.326839Z digest=sha256:f6250b2740c5d373a75ff93c1eaf6fbf9c2f2be81e4010b6056bb5ad049831db

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.329571Z digest=sha256:1fb61f471b3012887243402d602d69d43bc78ac400ad34b97d42c64d1d08453b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.332270Z digest=sha256:9970a79ac44a5e33da1ac5858f04a8526cf550959c946e10629a9e81edaa9990

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:37:40.335187Z digest=sha256:72ceda0d3482eed8831873fcb7545ca7d5ee3f2b14032aaeeded698428b11d69

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.338671Z digest=sha256:674ce6dcf365cef9bcb291206877592fdd2dc68d4127546c9a95228f838ca4b5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.341832Z digest=sha256:9c1b3234ba53869c6f8282e94bcca7a9c6f047d3e6c0e000260aa920023fae7d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.344556Z digest=sha256:3cc080815ea546320b711d29ba9ba774b2c53d5291039a545404117113fb42df

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.347365Z digest=sha256:0132b1ff59320e5336b5cfd33e84560610775746938f2d43d1888373f488c423

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.350046Z digest=sha256:58b8ce1729f3804606287a53b5fc9992483396eabd822880495ce9e68369efd8

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.353675Z digest=sha256:1a5ba2c262f37312edfe468d146d29f55c895b40fad9dc39c5854d7a4b558283

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.356398Z digest=sha256:ba8b1a3c6ae22773c6842ffc014bd749abd2368f8ec492c4e1d7c5fad077b971

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.360050Z digest=sha256:dd49f35770a6ae59e1d60fbc32c5c8925689bf818a89ff5f4bd4470a7db92eec

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.363614Z digest=sha256:a24563da2b7fd6129fe5b385b09b60493d90351c354407eedbe3ae6cb8e0af31

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:37:40.366533Z digest=sha256:689e43e8e0414801ef96e102b287fccf6819b690ab8b64825bb45871861aee20

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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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 2026-08-10T06:31:04.303077+00:00.

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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
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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