Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization | Paper Citation Record

Observation 3cc03e8b-8fad-47a5-8ff7-9b6ae471cbf7 · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Meta-causal learning for single domain generalization,

Reference 1

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Observation 048af773-d90e-4177-9f1f-a2d3374394ee · outbound

This paper cites Causality inspired representation learning for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Causality inspired representation learning for domain generalization,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.781229Z

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Observation 508a68be-09ca-4e0f-9747-3c7bfa819fd4 · outbound

This paper cites Generalizing across domains via cross-gradient training,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Generalizing across domains via cross-gradient training,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.772824Z

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Observation fb60d997-2d85-45c3-827c-7075b5d749c9 · outbound

This paper cites Domain generalization using causal matching,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Domain generalization using causal matching,

Reference 4

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Observation e7433edf-03f3-4d4e-a001-36d9be7406b0 · outbound

This paper cites Learning to generate novel domains for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Learning to generate novel domains for domain generalization,

Reference 5

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Observation 73fa2bea-0fb7-47fb-8bf2-fdbe24df609b · outbound

This paper cites Reducing domain gap by reducing style bias,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Reducing domain gap by reducing style bias,

Reference 6

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Observation 41f430b5-4c81-4007-bf8d-4f0c85f4e479 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Learning transferable visual models from natural language supervision,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.741052Z

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Observation 2bceef46-bc34-4794-995a-029dd969b3ae · outbound

This paper cites Promptstyler: Prompt-driven style generation for source-free domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Promptstyler: Prompt-driven style generation for source-free domain generalization,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.731406Z

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Observation 05146cde-33ce-46ac-ab0f-c0ea7a1b524a · outbound

This paper cites Learning common and specific visual prompts for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Learning common and specific visual prompts for domain generalization,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.723335Z

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Observation 179fa470-9bc6-47c6-a09c-5b6ccab9ca32 · outbound

This paper cites Domain-Unified Prompt Representations for Source-Free Domain Generalization.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Domain-Unified Prompt Representations for Source-Free Domain Generalization

Reference 10

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Observation 89037425-aed1-4937-8b99-6a51e8297ebb · outbound

This paper cites A closer look at the robustness of contrastive language-image pre-training (clip),.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization A closer look at the robustness of contrastive language-image pre-training (clip),

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.715241Z

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Observation 3e3e6d2a-b5ff-41ab-88de-b4f0db4aedb3 · outbound

This paper cites Test-time adaptation with CLIP reward for zero-shot generalization in vision-language models,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Test-time adaptation with CLIP reward for zero-shot generalization in vision-language models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.706720Z

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Observation f1015232-62ac-4a03-ad54-00d7786dde34 · outbound

This paper cites Achieving plasticity- stability trade-off in continual learning through adaptive orthogonal projection,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Achieving plasticity- stability trade-off in continual learning through adaptive orthogonal projection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.698244Z

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Observation d733e97e-5187-4ed8-b504-19e213708f2c · outbound

This paper cites Progressive negative enhancing contrastive learning for image dehazing and beyond,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Progressive negative enhancing contrastive learning for image dehazing and beyond,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.690384Z

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Observation b1399dce-8342-471c-a51b-29a420d602b8 · outbound

This paper cites Continual all-in-one adverse weather removal with knowledge replay on a unified network structure,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Continual all-in-one adverse weather removal with knowledge replay on a unified network structure,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.682384Z

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Observation 91a15b0f-a750-41d7-9b54-b69b36023576 · outbound

This paper cites Alpha-clip: A clip model focusing on wherever you want,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Alpha-clip: A clip model focusing on wherever you want,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.674431Z

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Observation 49adde53-9829-4f58-9d20-b41f75d7e2b0 · outbound

This paper cites Grounded text-to-image synthesis with attention refocusing,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Grounded text-to-image synthesis with attention refocusing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.666220Z

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Observation 84bb331e-bb84-4d4b-ae29-d8ea1d37d20e · outbound

This paper cites TOAST: Transfer Learning via Attention Steering.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization TOAST: Transfer Learning via Attention Steering

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T16:42:42.982437Z

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Observation 0c30a181-425d-4ef7-a1db-d1dde4971fe9 · outbound

This paper cites Primecomposer: Faster progressively combined diffusion for image composition with attention steering,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Primecomposer: Faster progressively combined diffusion for image composition with attention steering,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.658370Z

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Observation ef66086a-733b-4987-a1c9-6e7c0c27f0ff · outbound

This paper cites xecgnet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization xecgnet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.649719Z

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Observation 511cb988-0bde-4d8f-b736-0474e1aab519 · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Learning to diversify for single domain generalization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.641524Z

Source-reported events for the cited work

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Observation eb3579ef-d755-442c-96b1-ced400476b6f · outbound

This paper cites Learning to learn single domain gen- eralization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Learning to learn single domain gen- eralization,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.632880Z

Source-reported events for the cited work

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Observation 676a2712-5b7f-4241-979d-13f0a8c828ba · outbound

This paper cites Representation enhancement-stabilization: Reducing bias-variance of domain general- ization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Representation enhancement-stabilization: Reducing bias-variance of domain general- ization,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.624464Z

Source-reported events for the cited work

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Observation d5069ad8-3c79-46a2-9316-071362ffaea5 · outbound

This paper cites Poem: polarization of embeddings for domain- invariant representations,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Poem: polarization of embeddings for domain- invariant representations,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.615624Z

Source-reported events for the cited work

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Observation 174dd888-08c5-44de-bdf6-4cafd273b657 · outbound

This paper cites Adversarial invariant feature learning with accuracy constraint for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Adversarial invariant feature learning with accuracy constraint for domain generalization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.607645Z

Source-reported events for the cited work

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Observation 8e8853ff-6749-46d9-9076-502dd26128c3 · outbound

This paper cites Grounding stylistic domain generalization with quantitative domain shift measures and synthetic scene images,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Grounding stylistic domain generalization with quantitative domain shift measures and synthetic scene images,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.598461Z

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Observation a77f17e7-c8f7-4938-bbf2-9cafa22602e7 · outbound

This paper cites Self-challenging improves cross-domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Self-challenging improves cross-domain generalization,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.589147Z

Source-reported events for the cited work

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Observation 802c125c-4847-44da-92a3-31bfd5ef0327 · outbound

This paper cites Gradient matching for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Gradient matching for domain generalization,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.580704Z

Source-reported events for the cited work

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Observation 8ad2f8fb-e814-45f1-8b04-80145ef54c52 · outbound

This paper cites Dna: Domain generalization with diversified neural averaging,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Dna: Domain generalization with diversified neural averaging,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.571950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 31309960-29d1-4c58-a678-34f67f5163ac · outbound

This paper cites Sharpness-aware gradient matching for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Sharpness-aware gradient matching for domain generalization,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.563690Z

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Observation 5bee260c-ce43-4568-afff-f95919271f88 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.555153Z

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Observation 3c5a0f18-554f-45d2-84b8-4ddcb1a37f59 · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization High- resolution image synthesis with latent diffusion models,

Reference 32

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Observation cfcd71c0-ed8a-4217-bee6-20428b78d713 · outbound

This paper cites A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation

Reference 33

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Observation 718cf79a-1ad5-492a-a8e4-fc959ea6ca01 · outbound

This paper cites Data-free generalized zero-shot learning,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Data-free generalized zero-shot learning,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.541485Z

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Observation 64774214-9e40-41bf-bc4a-e5f408416c13 · outbound

This paper cites Disentangled prompt representation for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Disentangled prompt representation for domain generalization,

Reference 35

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Observation 0d653bf4-cba1-4612-b15c-1ada304db903 · outbound

This paper cites Dual modality prompt tuning for vision-language pre-trained model,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Dual modality prompt tuning for vision-language pre-trained model,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.525426Z

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Observation 07997096-a760-4c80-84ff-ff0e37011db0 · outbound

This paper cites Captions Are Worth a Thousand Words: Enhancing Product Retrieval with Pretrained Image-to-Text Models.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Captions Are Worth a Thousand Words: Enhancing Product Retrieval with Pretrained Image-to-Text Models

Reference 37

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Observation 33cf808c-8cea-4ddb-b0c4-731b6050b23a · outbound

This paper cites Embracing language inclusivity and diversity in clip through continual language learning,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Embracing language inclusivity and diversity in clip through continual language learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.516360Z

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Observation 8ec7313a-7ae6-456f-a2e4-32e4b4783a18 · outbound

This paper cites Clippo: Image-and- language understanding from pixels only,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Clippo: Image-and- language understanding from pixels only,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.507766Z

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Observation b1dd7871-fc68-48ba-8cb8-97f9e5554cf6 · outbound

This paper cites Linearly mapping from image to text space,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Linearly mapping from image to text space,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.499612Z

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Observation d86c786c-60d3-462a-9be7-3d8a10829b4c · outbound

This paper cites Exploring homogeneous and heterogeneous consistent label associations for unsupervised visible- infrared person reid,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Exploring homogeneous and heterogeneous consistent label associations for unsupervised visible- infrared person reid,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.491591Z

Source-reported events for the cited work

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Observation eb374730-2600-45f2-814c-8e6b742e92ef · outbound

This paper cites Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:42:43.204670Z

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Observation c3c92711-d520-4656-bead-ab88ce38e2f0 · outbound

This paper cites Stylip: Multi-scale style-conditioned prompt learning for clip-based domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Stylip: Multi-scale style-conditioned prompt learning for clip-based domain generalization,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.483587Z

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Observation 7b7cdbf6-61a3-41b4-877a-8adc341c43d5 · outbound

This paper cites Visual prompt tuning,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Visual prompt tuning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.475479Z

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Observation 44d4dbf6-28e8-4436-b7f9-48c08fb61185 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T16:42:43.056454Z

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Observation dc3c39ec-9277-47dd-810a-cf1a36ece235 · outbound

This paper cites Attention is all you need,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Attention is all you need,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.461741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5ffda7f9-00f1-4b1a-9d8e-bf0a73433c0b · outbound

This paper cites Regionclip: Region-based language-image pretraining,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Regionclip: Region-based language-image pretraining,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.454102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b8e422e9-7b6a-4d65-a7bc-fcd878e604ae · outbound

This paper cites Masqclip for open-vocabulary universal image segmentation,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Masqclip for open-vocabulary universal image segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.445717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3e3ceedd-101e-4c71-8aff-953abde145f9 · outbound

This paper cites Open- vocabulary panoptic segmentation with text-to-image diffusion models,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Open- vocabulary panoptic segmentation with text-to-image diffusion models,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.437581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7fc963f9-1ef0-4835-9852-73e5007491c6 · outbound

This paper cites Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:42:43.193106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88b4bdfe-871e-43e5-bbcc-423cbd4431d3 · outbound

This paper cites Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:42:43.179868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7b72934e-9bd7-41c5-9646-3b61143b7ead · outbound

This paper cites Attention diversification for domain gen- eralization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Attention diversification for domain gen- eralization,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.429593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 73410294-dd4d-456f-82d0-1447733809bf · outbound

This paper cites Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.421616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da1b46ae-7acb-435f-9d9e-d055806d76f1 · outbound

This paper cites Deeper, broader and artier domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Deeper, broader and artier domain generalization,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.413966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4cfc6c65-b832-4e91-bc61-9fb05e797bff · outbound

This paper cites Deep hashing network for unsupervised domain adaptation,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Deep hashing network for unsupervised domain adaptation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.406270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f3562c9f-9b5d-425c-bef2-e511c8567857 · outbound

This paper cites Recognition in terra incognita,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Recognition in terra incognita,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.398540Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1153883d-214d-4490-9932-3e1307285a6a · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Moment matching for multi-source domain adaptation,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.390592Z

Source-reported events for the cited work

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Observation a2704de0-bbf7-46a1-98e9-27afa896d050 · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization The pascal visual object classes (voc) challenge,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.382736Z

Source-reported events for the cited work

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Observation 9d10f16c-8eac-4acd-be53-c5331b0f4181 · outbound

This paper cites Labelme: a database and web-based tool for image annotation,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Labelme: a database and web-based tool for image annotation,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.374998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bd5acb7f-fd2a-4399-a89e-18b8c3597f61 · outbound

This paper cites Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.366991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 29ee3319-8d0a-454e-80c7-4bf0706cd11d · outbound

This paper cites Sun database: Large-scale scene recognition from abbey to zoo,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Sun database: Large-scale scene recognition from abbey to zoo,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.357666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fe5f02de-d52f-4253-8389-e98a5895116b · outbound

This paper cites In Search of Lost Domain Generalization.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization In Search of Lost Domain Generalization

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T16:42:43.103846Z

Source-reported events for the cited work

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Observation f9dad549-6dad-4e26-9f10-2dfd0f4dd809 · outbound

This paper cites Soft prompt generation for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Soft prompt generation for domain generalization,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.349963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b82968d4-4997-4ccf-9495-4875f3cf92b8 · outbound

This paper cites Maple: Multi-modal prompt learning,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Maple: Multi-modal prompt learning,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.341492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8889f7b8-900c-45f4-866b-1668194403d3 · outbound

This paper cites Statistical learning theory,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Statistical learning theory,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.333434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fcc504a4-65aa-4da1-b3cf-1c28b4f63400 · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Domain-adversarial training of neural networks,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.325252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b092507c-d7d6-4f29-a34f-92fc57790643 · outbound

This paper cites Deep coral: Correlation alignment for deep domain adaptation,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Deep coral: Correlation alignment for deep domain adaptation,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.316888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a1e4860b-43b5-425f-9903-70277b8d3969 · outbound

This paper cites Domain generalization by mutual- information regularization with pre-trained models,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Domain generalization by mutual- information regularization with pre-trained models,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.308055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6e6b57fb-8e9c-4ae0-8005-687a22a09e05 · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Clip-adapter: Better vision-language models with feature adapters,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.299104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 25911a3e-97c6-45cc-9acd-ee7f27f892b3 · outbound

This paper cites Gallop: Learning global and local prompts for vision-language models,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Gallop: Learning global and local prompts for vision-language models,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.290360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 90a8728e-429c-4983-82d7-57eca99352f3 · outbound

This paper cites Clipceil: Domain generalization through clip via channel refinement and image-text alignment,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Clipceil: Domain generalization through clip via channel refinement and image-text alignment,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.281622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ee2cf425-9a1a-4860-bef5-0606ea23b06c · outbound

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

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization A fourier-based framework for domain generalization,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.273217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 03b5987e-732a-48e5-94e1-98760bcb7ff3 · outbound

This paper cites Robust and generalizable visual representation learning via random convolutions,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Robust and generalizable visual representation learning via random convolutions,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.264732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation af6c6e28-4521-4e9a-884f-98aebeee61ef · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T16:42:43.137003Z

Source-reported events for the cited work

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Observation db6abaaa-2301-4c70-97d1-8f733e20a8cb · outbound

This paper cites Nico++: Towards better benchmarking for domain generalization,.

Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization Nico++: Towards better benchmarking for domain generalization,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:42:43.249719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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