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Paper Citation Record · LEDGER

Target-Oriented Single Domain Generalization

As of 12 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2509.00351.

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

pith.paper-citation-record.v1
2509.00351 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:45:58.006475Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

  • verified exact2
  • verified fuzzy39
  • unresolved3
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7cf7f9d4-b99e-4f81-ab5e-b812f5eb5e04 · outbound

This paper cites Generalizing to unseen domains via adversarial data augmentation,.

Target-Oriented Single Domain Generalization Generalizing to unseen domains via adversarial data augmentation,

Reference 1

Resolution
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Source-reported events for the cited work

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Observation 23d45712-f9b8-441a-b121-0093ef3f8083 · outbound

This paper cites Learning to learn single domain generalization,.

Target-Oriented Single Domain Generalization Learning to learn single domain generalization,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 5ac2931a-fed0-47f7-b3a1-ae0f4047eb74 · outbound

This paper cites In search of lost domain generalization,.

Target-Oriented Single Domain Generalization In search of lost domain generalization,

Reference 3

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Source-reported events for the cited work

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Observation 0fcd8a3b-6f2d-47aa-9c6d-dd254a4f7e64 · outbound

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

Target-Oriented Single Domain Generalization Learning transferable visual models from natural language supervi- sion,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation f94a5b56-5f8b-4262-b765-b58865ea0da0 · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.

Target-Oriented Single Domain Generalization Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ddb50bc0-fa38-483f-8484-5015f7464925 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

Target-Oriented Single Domain Generalization Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 67c2c9c4-9b3a-47f2-844b-f35a824ac0fc · outbound

This paper cites Learning to prompt for vision-language models,.

Target-Oriented Single Domain Generalization Learning to prompt for vision-language models,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 068fdd0b-0e36-4e1c-ade6-6d432977e1d2 · outbound

This paper cites Conditional prompt learning for vision-language mod- els,.

Target-Oriented Single Domain Generalization Conditional prompt learning for vision-language mod- els,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c5df718a-5087-4b7d-9332-a843392a4a03 · outbound

This paper cites Clip-adapter: Better vision-language models with feature adapters,.

Target-Oriented Single Domain Generalization Clip-adapter: Better vision-language models with feature adapters,

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 4cb57a0c-5129-4ff8-8925-553708bab2a2 · outbound

This paper cites Tip-adapter: Training- free adaption of clip for few-shot classification,.

Target-Oriented Single Domain Generalization Tip-adapter: Training- free adaption of clip for few-shot classification,

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ab4b6e7c-19db-4351-a354-8d4219ad99cb · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Target-Oriented Single Domain Generalization Improved Regularization of Convolutional Neural Networks with Cutout

Reference 11

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f35e1638-eb1c-4c80-8ebb-02c848045440 · outbound

This paper cites Augmix: A simple data processing method to improve robustness and uncertainty,.

Target-Oriented Single Domain Generalization Augmix: A simple data processing method to improve robustness and uncertainty,

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b8a50007-ac40-4042-90db-2bd7304efd21 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space,.

Target-Oriented Single Domain Generalization Randaugment: Practical automated data augmentation with a reduced search space,

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b4943094-e44a-4bcd-b361-167ed61f4188 · outbound

This paper cites Exploring Geometric Consistency for Monocular 3D Object Detection.

Target-Oriented Single Domain Generalization Exploring Geometric Consistency for Monocular 3D Object Detection

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9655ac9d-a21c-4c93-a41a-68a5c15910f9 · outbound

This paper cites Attention consistency on visual corruptions for single-source domain generalization,.

Target-Oriented Single Domain Generalization Attention consistency on visual corruptions for single-source domain generalization,

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 7531fa01-dfb3-4240-add3-ff4b3907bece · outbound

This paper cites Maximum-entropy adversarial data augmentation for improved generalization and robustness,.

Target-Oriented Single Domain Generalization Maximum-entropy adversarial data augmentation for improved generalization and robustness,

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 54fc43ea-20c3-4c30-83cb-e9ae9ea52bcb · outbound

This paper cites Adversarial autoaugment,.

Target-Oriented Single Domain Generalization Adversarial autoaugment,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 024a0bda-3119-4641-9b21-37aabab5b7e0 · outbound

This paper cites Adversarial style augmentation for domain generalization,.

Target-Oriented Single Domain Generalization Adversarial style augmentation for domain generalization,

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 2d34a5d8-cdd6-46aa-bc76-5b7d1fde5e20 · outbound

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

Target-Oriented Single Domain Generalization Learning to diversify for single domain generalization,

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e922c3db-998c-44de-9137-3bb0d705f220 · outbound

This paper cites Progressive domain expansion network for single domain generalization,.

Target-Oriented Single Domain Generalization Progressive domain expansion network for single domain generalization,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1c219b5d-7c1f-4b1f-a9a8-0ed335fd4ddb · outbound

This paper cites Advst: Revisiting data augmentations for single domain generalization,.

Target-Oriented Single Domain Generalization Advst: Revisiting data augmentations for single domain generalization,

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0c74734f-4730-4b2c-aa34-087874615d4b · outbound

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

Target-Oriented Single Domain Generalization Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 4bbfd452-4db7-4836-89ca-8586b2b82e13 · outbound

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

Target-Oriented Single Domain Generalization Iterative normalization: Beyond standardization towards efficient whitening,

Reference 23

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 7038ce5d-1957-482c-bc1d-5371ff0dcfad · outbound

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

Target-Oriented Single Domain Generalization Two at once: Enhancing learning and generalization capacities via ibn-net,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 37640001-e055-48ab-9278-0de886a0477e · outbound

This paper cites Switchable whitening for deep representation learning,.

Target-Oriented Single Domain Generalization Switchable whitening for deep representation learning,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation eb823224-8985-4f97-92ff-620a108e8c66 · outbound

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

Target-Oriented Single Domain Generalization Robustnet: Improving domain generalization in urban-scene segmentation via instance selective whitening,

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 70b6824d-993f-41c8-8e4f-54f3d2971538 · outbound

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

Target-Oriented Single Domain Generalization Single-domain generalized object detection in urban scene via cyclic- disentangled self-distillation,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ade71a79-dc18-4894-b93d-c2b369d65afa · outbound

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

Target-Oriented Single Domain Generalization Clip the gap: A single domain generalization approach for object detection,

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b38f7e88-5ee7-4de4-9fc1-4f37e3a693d1 · outbound

This paper cites Exploring the limits of out-of-distribution detection,.

Target-Oriented Single Domain Generalization Exploring the limits of out-of-distribution detection,

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a965ff41-a800-469c-82c2-b3dc13093e68 · outbound

This paper cites Towards Unified and Effective Domain Generalization.

Target-Oriented Single Domain Generalization Towards Unified and Effective Domain Generalization

Reference 30

Resolution
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local_arxiv, observed 2026-08-05T13:45:58.198021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 117169f0-edec-46d7-b26b-a9e80ebd9ca8 · outbound

This paper cites Clipood: Generalizing clip to out-of-distributions,.

Target-Oriented Single Domain Generalization Clipood: Generalizing clip to out-of-distributions,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:46:00.879810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 78686c62-b914-4c8e-ada0-17707b5bf859 · outbound

This paper cites Leveraging vision-language models for improving domain generalization in image classification,.

Target-Oriented Single Domain Generalization Leveraging vision-language models for improving domain generalization in image classification,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:46:00.748039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation cf66a6ba-2fb8-4b30-880f-4b8736f557d4 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance nor- malization,.

Target-Oriented Single Domain Generalization Arbitrary style transfer in real-time with adaptive instance nor- malization,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:46:00.614841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0d431102-b8b8-4e1f-a83d-a3c293c12249 · outbound

This paper cites mixup: Beyond empirical risk minimization,.

Target-Oriented Single Domain Generalization mixup: Beyond empirical risk minimization,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:46:00.479011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 62fe8a3a-3925-4d50-b6ff-884525ef719c · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features,.

Target-Oriented Single Domain Generalization Cutmix: Regularization strategy to train strong classifiers with localizable features,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:46:00.291458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.109375Z digest=sha256:0e24e24aca5043e3b4a69d3eae6491082a119923c0b544cad1a99dd020b1a526

Observation 2d252a35-5512-4bfe-870a-bee06528ae69 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space,.

Target-Oriented Single Domain Generalization Randaugment: Practical automated data augmentation with a reduced search space,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:46:00.152263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.222507Z digest=sha256:1437b74c4297f4ecc6b4219ff0f320654903fdec9b7b83dff0c414a93f54bf7e

Observation 6bce9629-6173-49d5-ac41-1c49f883b525 · outbound

This paper cites Deeper, broader and artier domain general- ization,.

Target-Oriented Single Domain Generalization Deeper, broader and artier domain general- ization,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:59.904287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.305267Z digest=sha256:e16a9694de272b32da56e3e7a469e20c98240afdb62c885c383e2d5d9a7aace1

Observation ebc72009-79d2-4646-9957-67f121d49270 · outbound

This paper cites Moment matching for multi- source domain adaptation,.

Target-Oriented Single Domain Generalization Moment matching for multi- source domain adaptation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:59.744517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.367076Z digest=sha256:599bb8517845827c6ad0a201c5401950d08d27ed6f4e8b9d5d6b4c5aacbdc483

Observation fba6a80d-0574-45db-ab64-eb6a5a45f794 · outbound

This paper cites AutoAugment: Learning Augmentation Policies from Data.

Target-Oriented Single Domain Generalization AutoAugment: Learning Augmentation Policies from Data

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:57.475850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:57.475850Z digest=sha256:16b11b34bacab2b633b650db046367542d04f13d36bd3e2966f10e3c6ebecf29

Observation 8f5d04c6-4435-4e85-936b-543fd1aca978 · outbound

This paper cites Koltchinskii,Oracle inequalities in empirical risk minimization and sparse recovery problems: École D’Été de Probabilités de Saint-Flour XXXVIII-2008.

Target-Oriented Single Domain Generalization Koltchinskii,Oracle inequalities in empirical risk minimization and sparse recovery problems: École D’Été de Probabilités de Saint-Flour XXXVIII-2008

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:59.581261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.568857Z digest=sha256:43ea517d5d9d75fa39d3a2de3667cbb403ef1a0246d5048041e9999a4edf8a51

Observation 99dbc754-f30b-49ff-867f-819e066f36b3 · outbound

This paper cites Unified deep supervised domain adaptation and generalization,.

Target-Oriented Single Domain Generalization Unified deep supervised domain adaptation and generalization,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:59.417594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.668177Z digest=sha256:c14734dc3323d74c9236da6ee8fe0efb2d4209acc8096200684abc27685fb929

Observation 8a7287c0-0d11-4df5-b875-362617cb2b0d · outbound

This paper cites Domain generaliza- tion by solving jigsaw puzzles,.

Target-Oriented Single Domain Generalization Domain generaliza- tion by solving jigsaw puzzles,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:59.178284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.759756Z digest=sha256:41d76fc6d253c3e785b4a39d6768b29a7be7f33ffa69504cf3b0c39fbb605daa

Observation 140b7f01-3f8a-4a7d-bb7b-7377bd35bd96 · outbound

This paper cites Addressing model vulnerability to distributional shifts over image transformation sets,.

Target-Oriented Single Domain Generalization Addressing model vulnerability to distributional shifts over image transformation sets,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:58.976788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.834755Z digest=sha256:38f2cfe7d2083cead2e29d02b1b130e599a124e41ce061604997f69da2dd8bc1

Observation ac8f9883-865c-4350-95ef-ccd55f9e7d98 · outbound

This paper cites Visual instruction tuning,.

Target-Oriented Single Domain Generalization Visual instruction tuning,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:58.775302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:57.928275Z digest=sha256:33e6b6e79c6d80b38453ac06fe28253199671c63f37c7d8549c3897d4c4e9bd7

Observation f7629048-7364-4dab-9c91-99227e55cac8 · outbound

This paper cites Deep residual learning for image recognition,.

Target-Oriented Single Domain Generalization Deep residual learning for image recognition,

Reference 45

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T13:45:58.606333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:45:58.006475Z digest=sha256:fb637a9eb2c52c5c0ead2670505b65522e71a6fe2568deccea3ff3bcb7656978

Pith citing papers

No inbound Pith citation observations are available.