BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization | Paper Citation Record

Observation 18b9f31f-8015-4558-b4b8-937966867102 · outbound

This paper cites Solid: minimizing tissue distortion for brain-wide profiling of diverse architec- tures,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Solid: minimizing tissue distortion for brain-wide profiling of diverse architec- tures,

Reference 1

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Observation ae1c38cb-4a51-4437-a392-c234e970f6cd · outbound

This paper cites V oxelmorph: A learning framework for deformable medical image registration,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization V oxelmorph: A learning framework for deformable medical image registration,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.699028Z

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This paper cites Deep residual learning for image recognition,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Deep residual learning for image recognition,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.687861Z

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This paper cites Imagenet classification with deep convolutional neural networks,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Imagenet classification with deep convolutional neural networks,

Reference 4

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This paper cites Very deep convolu- tional networks for large-scale image recognition,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Very deep convolu- tional networks for large-scale image recognition,

Reference 5

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Observation 2b9e173c-03c2-42c7-84dd-48c8410f9eed · outbound

This paper cites Application of medical image detection tech- nology based on deep learning in pneumoconiosis diag- nosis,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Application of medical image detection tech- nology based on deep learning in pneumoconiosis diag- nosis,

Reference 6

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This paper cites Densely connected convolutional networks,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Densely connected convolutional networks,

Reference 7

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Observation c9c48637-7667-4055-b14f-bce0e15e4b00 · outbound

This paper cites Residual attention network for image classification,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Residual attention network for image classification,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.630546Z

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Observation 3466ed6c-5fec-4b72-8b4d-93150be45295 · outbound

This paper cites End-to-end object detection with transformers,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization End-to-end object detection with transformers,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.619157Z

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Observation 623b0aff-72b2-40f4-b85e-8e28c914a861 · outbound

This paper cites Faster R-CNN: towards real-time object detection with region proposal networks,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Faster R-CNN: towards real-time object detection with region proposal networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.608333Z

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Observation 4197febc-f9f2-4324-a787-daeb45d82720 · outbound

This paper cites One-shot adaptation of supervised deep convolutional models,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization One-shot adaptation of supervised deep convolutional models,

Reference 11

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Observation 249ebae9-51d3-4bba-bf2a-c82b3348a2b7 · outbound

This paper cites Fifo: Learning fog- invariant features for foggy scene segmentation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Fifo: Learning fog- invariant features for foggy scene segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.586515Z

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Observation 4b666b88-4654-45aa-9f39-80558883854b · outbound

This paper cites Semi-supervised domain adaptation via minimax en- tropy,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Semi-supervised domain adaptation via minimax en- tropy,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.575694Z

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Observation 839037b5-df76-4d41-8b2f-f330e4de9c78 · outbound

This paper cites Domain generalization via encoding and resampling in a unified latent space,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Domain generalization via encoding and resampling in a unified latent space,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.564337Z

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This paper cites Style nor- malization and restitution for domain generalization and adaptation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Style nor- malization and restitution for domain generalization and adaptation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.552829Z

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Observation 74e29964-6960-4dae-b768-09fa67be878c · outbound

This paper cites A novel mix- normalization method for generalizable multi-source per- son re-identification,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization A novel mix- normalization method for generalizable multi-source per- son re-identification,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.540947Z

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Observation c7b2cd2f-aabf-41eb-b5fc-df9dcec2f99b · outbound

This paper cites Learning features of intra-consistency and inter-diversity: Keys toward gen- eralizable deepfake detection,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Learning features of intra-consistency and inter-diversity: Keys toward gen- eralizable deepfake detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.528901Z

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Observation 39393627-ef7e-40c8-9571-35b6aae58187 · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Prompt- styler: Prompt-driven style generation for source-free domain generalization,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.516112Z

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Observation 16e4db07-0e21-4730-8615-41825759d41f · outbound

This paper cites Towards data-free domain generalization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Towards data-free domain generalization,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.505311Z

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Observation 8cb9fcf7-d487-4e36-ba26-14a69ce65025 · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Domain-Unified Prompt Representations for Source-Free Domain Generalization

Reference 20

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Observation 6c07ec9f-bf8f-49cf-84ee-c69f59ab99e4 · outbound

This paper cites Generalize then adapt: Source-free domain adaptive semantic segmentation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Generalize then adapt: Source-free domain adaptive semantic segmentation,

Reference 21

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Observation 42703cca-bc5f-4304-9029-833843312ab0 · outbound

This paper cites Source- free unsupervised domain adaptation: A survey,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Source- free unsupervised domain adaptation: A survey,

Reference 22

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Observation 015eaeff-7f00-48c3-befb-de9f96b2313f · outbound

This paper cites Model adap- tation: Historical contrastive learning for unsupervised domain adaptation without source data,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Model adap- tation: Historical contrastive learning for unsupervised domain adaptation without source data,

Reference 23

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Observation d8434164-9428-44b4-99ca-68fe32d2b79c · outbound

This paper cites Source-free domain adaptation with frozen multimodal foundation model,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Source-free domain adaptation with frozen multimodal foundation model,

Reference 24

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Observation e442f3ce-d5d3-4bcf-b7da-ed96db442fbd · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Learning transferable visual models from natural language supervision,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.451379Z

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Observation 1c69613a-9178-4df7-9eff-9a6a23084063 · outbound

This paper cites Adversarially adaptive normalization for single domain generalization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Adversarially adaptive normalization for single domain generalization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.440488Z

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Observation 7498d406-8e93-40b7-82bf-ffcc0d8c2d75 · outbound

This paper cites Learning to learn single domain generalization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Learning to learn single domain generalization,

Reference 27

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Observation 484a02bb-d25b-4d2b-a8d6-e996c59a3c3a · outbound

This paper cites Generalized semi-supervised and structured subspace learning for cross-modal retrieval,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Generalized semi-supervised and structured subspace learning for cross-modal retrieval,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.419732Z

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Observation f58317e0-a1a3-4380-beb1-95b66e18c387 · outbound

This paper cites Three heads better than one: Pure entity, relation label and adversarial training for cross-domain few-shot relation extraction,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Three heads better than one: Pure entity, relation label and adversarial training for cross-domain few-shot relation extraction,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.409139Z

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Observation 1b3e2d3e-e225-499b-b29d-a5bde93b4214 · outbound

This paper cites Reduc- ing domain gap by reducing style bias,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Reduc- ing domain gap by reducing style bias,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.398958Z

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Observation 7dc71dfe-f8fe-402c-8e3b-5b11329f082d · outbound

This paper cites Permuted adain: Reducing the bias towards global statistics in image classification,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Permuted adain: Reducing the bias towards global statistics in image classification,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.388781Z

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Observation 576496d6-ddc3-449e-8f1b-d13e5523c374 · outbound

This paper cites Domain Generalization via Optimal Transport with Metric Similarity Learning.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Domain Generalization via Optimal Transport with Metric Similarity Learning

Reference 32

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Observation 39078703-3c9c-4f83-b049-9b140649a1c9 · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Moment matching for multi-source domain adaptation,

Reference 33

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Observation 31b3178d-d483-400e-baf7-bdca0c104d0a · outbound

This paper cites 3d-aided deep pose-invariant face recogni- tion,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization 3d-aided deep pose-invariant face recogni- tion,

Reference 34

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Observation 0837e4b2-089c-4109-bc2a-a09948bc7212 · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Two at once: Enhancing learning and generalization capacities via ibn-net,

Reference 35

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Observation f84843ca-4ab5-47cb-9f47-1e49245f8974 · outbound

This paper cites Frustratingly easy person re-identification: Generalizing person re-id in practice,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Frustratingly easy person re-identification: Generalizing person re-id in practice,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.345409Z

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Observation b780136c-144a-4905-b0ef-819114311e0f · outbound

This paper cites Cross-modal data augmentation for tasks of different modalities,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Cross-modal data augmentation for tasks of different modalities,

Reference 37

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Observation bef79f07-749b-48a3-af37-7c2050fc097d · outbound

This paper cites Dual-agent gans for photorealistic and identity preserving profile face synthesis,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Dual-agent gans for photorealistic and identity preserving profile face synthesis,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.325188Z

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Observation 75de6238-22b2-4e51-811e-e49dc80c12ce · outbound

This paper cites Look across elapse: Disen- tangled representation learning and photorealistic cross- age face synthesis for age-invariant face recognition,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Look across elapse: Disen- tangled representation learning and photorealistic cross- age face synthesis for age-invariant face recognition,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.315235Z

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Observation 870f7bc5-7f7a-49f1-a431-d7d478999d8d · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.305661Z

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Observation 76abe8f4-c240-4aea-99c8-d55d44920500 · outbound

This paper cites BLIP: boot- strapping language-image pre-training for unified vision- language understanding and generation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization BLIP: boot- strapping language-image pre-training for unified vision- language understanding and generation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.296050Z

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Observation 06417bac-f358-4fdf-ab39-d6dcbb48d97a · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 42

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Observation 568beb63-0a6a-40c7-93c1-692936a1455b · outbound

This paper cites Faster zero-shot multi-modal entity linking via visual-linguistic representation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Faster zero-shot multi-modal entity linking via visual-linguistic representation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.285729Z

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Observation dc3baaa6-0c60-4b00-90b6-c302dd59deac · outbound

This paper cites Diagnosing and rectifying vision models using language,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Diagnosing and rectifying vision models using language,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.275743Z

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Observation e0aab298-914e-4164-a422-c00503ef8b17 · outbound

This paper cites Prevalence of neural collapse during the terminal phase of deep learning training,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Prevalence of neural collapse during the terminal phase of deep learning training,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.265892Z

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Observation 84a57ac7-296a-4dbf-95ca-68ee27930d6d · outbound

This paper cites Inducing neural collapse in imbalanced learning: Do we really need a learnable classifier at the end of deep neural network?.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Inducing neural collapse in imbalanced learning: Do we really need a learnable classifier at the end of deep neural network?

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.256042Z

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Observation 593fbbce-0d60-478d-bb61-744e218aa53a · outbound

This paper cites Neural collapse in- spired attraction-repulsion-balanced loss for imbalanced learning,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Neural collapse in- spired attraction-repulsion-balanced loss for imbalanced learning,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.245475Z

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Observation dcbb0999-bf56-4406-889b-f405a5babece · outbound

This paper cites Targeted representation alignment for open-world semi-supervised learning,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Targeted representation alignment for open-world semi-supervised learning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.235114Z

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Observation 1a6ed71a-bf5d-4edd-af1a-08e1e1a5dc2b · outbound

This paper cites Neural collapse inspired semi-supervised learning with fixed classifier,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Neural collapse inspired semi-supervised learning with fixed classifier,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.225285Z

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Observation 193609b5-0f5b-4a56-a77c-cc4aba8c8d70 · outbound

This paper cites Learning optimal inter-class margin adaptively for few- shot class-incremental learning via neural collapse-based meta-learning,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Learning optimal inter-class margin adaptively for few- shot class-incremental learning via neural collapse-based meta-learning,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.214686Z

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Observation 1c007cc7-ab75-4832-8e73-dffe108d7a64 · outbound

This paper cites Neural collapse inspired feature-classifier alignment for few-shot class-incremental learning,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Neural collapse inspired feature-classifier alignment for few-shot class-incremental learning,

Reference 51

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Observation b30a6a37-3d77-40ae-9c3b-08c0c77850bf · outbound

This paper cites Neural collapse anchored prompt tuning for generalizable vision-language models,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Neural collapse anchored prompt tuning for generalizable vision-language models,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.194211Z

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Observation f08f73ab-5644-4633-9765-d2cb5601a2b8 · outbound

This paper cites Understanding Prompt Tuning for V-L Models Through the Lens of Neural Collapse.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Understanding Prompt Tuning for V-L Models Through the Lens of Neural Collapse

Reference 53

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Observation 5ecd2611-cb49-44ff-b112-bf50c47a2848 · outbound

This paper cites k-means++: the advan- tages of careful seeding,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization k-means++: the advan- tages of careful seeding,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.183304Z

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Observation 68e3fda2-64a2-4a15-ae08-3500aca48dcc · outbound

This paper cites GPT-4 Technical Report.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization GPT-4 Technical Report

Reference 55

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Observation 4c3dba08-59b7-4d1d-93dd-3f5d27205589 · outbound

This paper cites Arcface: Ad- ditive angular margin loss for deep face recognition,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Arcface: Ad- ditive angular margin loss for deep face recognition,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.173398Z

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Observation 43646a87-affd-4bc2-b7e3-bc2ab86214d6 · outbound

This paper cites Learning class and domain augmen- tations for single-source open-domain generalization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Learning class and domain augmen- tations for single-source open-domain generalization,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.162806Z

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Observation 1cd82915-39eb-46da-9a80-2de980f1d88b · outbound

This paper cites Exploring ex- plicitly disentangled features for domain generalization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Exploring ex- plicitly disentangled features for domain generalization,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.151692Z

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Observation 2c1db776-5488-45c0-9ceb-4835d0b9ad64 · outbound

This paper cites Normaug: Normalization-guided augmentation for domain general- ization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Normaug: Normalization-guided augmentation for domain general- ization,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.140533Z

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Observation 9327bbc3-86bc-469c-a7c7-41114ce7a422 · outbound

This paper cites Instance paradigm contrastive learning for domain gen- eralization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Instance paradigm contrastive learning for domain gen- eralization,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.129312Z

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Observation 49e541df-ee5a-403f-bdca-776cef506bb6 · outbound

This paper cites Source-free domain adaptation with unrestricted source hypothesis,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Source-free domain adaptation with unrestricted source hypothesis,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.118221Z

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Observation 4dc2ec97-400a-4b29-ad32-2f93d5bef773 · outbound

This paper cites Neighborhood-aware mutual information maximization for source-free domain adaptation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Neighborhood-aware mutual information maximization for source-free domain adaptation,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.107999Z

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Observation cdb27103-178e-4298-b044-ddb2daa0e9d7 · outbound

This paper cites Waffling around for performance: Visual classification with random words and broad concepts,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Waffling around for performance: Visual classification with random words and broad concepts,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.096689Z

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Observation ded3a1ca-1038-4670-b059-cd538f30ae18 · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Stylip: Multi-scale style-conditioned prompt learning for clip-based domain generalization,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.085943Z

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Observation 6cc0e57f-7665-4dc8-8b17-274df67ca640 · outbound

This paper cites PromptTA: Prompt-driven Text Adapter for Source-free Domain Generalization.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization PromptTA: Prompt-driven Text Adapter for Source-free Domain Generalization

Reference 65

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Observation f61bc81f-2197-4fae-807b-d896342a7d0c · outbound

This paper cites DPStyler: Dynamic PromptStyler for Source-Free Domain Generalization.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization DPStyler: Dynamic PromptStyler for Source-Free Domain Generalization

Reference 66

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Observation 43d717f1-481e-4e48-9ce3-9aeeb33bc853 · outbound

This paper cites Visual classification via description from large language models,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Visual classification via description from large language models,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.074730Z

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Observation bdc82bea-8f67-470c-acf3-bf2b7f797800 · outbound

This paper cites Chatgpt-powered hierarchi- cal comparisons for image classification,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Chatgpt-powered hierarchi- cal comparisons for image classification,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.063671Z

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Observation 4d941ec9-4bf7-4275-8300-aa7818da3467 · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Deeper, broader and artier domain generalization,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.052336Z

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Observation f4b13e68-1b34-4355-9a1f-69052102ae5b · outbound

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

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.040320Z

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Observation 76a58663-4010-4861-92bf-443b3f653417 · outbound

This paper cites Deep hashing network for unsupervised do- main adaptation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Deep hashing network for unsupervised do- main adaptation,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.029124Z

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Observation 604222d3-73cf-45a9-8b7c-906feb3028f8 · outbound

This paper cites The many faces of robustness: A critical analysis of out-of-distribution gen- eralization,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization The many faces of robustness: A critical analysis of out-of-distribution gen- eralization,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.018300Z

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Observation 7f131447-59b1-42ca-8a78-aeeb0d7a84e6 · outbound

This paper cites Large-scale unsupervised semantic segmentation,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Large-scale unsupervised semantic segmentation,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:13.006922Z

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Observation 23701df6-d067-4645-b86f-5f7abb24fd0f · outbound

This paper cites Visualizing data using t-sne,.

BatStyler: Advancing Multi-category Style Generation for Source-free Domain Generalization Visualizing data using t-sne,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:12.995489Z

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