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0bo
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0bo
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0bo
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0bo
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0bo
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0bo
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0bo
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0bo
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1brown-duck
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1brown-duck
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1brown-duck
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1brown-duck
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1brown-duck
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1brown-duck
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1brown-duck
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1brown-duck
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1brown-duck
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2butin
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2butin
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2butin
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2butin
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2butin
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3cat-cup
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3cat-cup
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3cat-cup
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3cat-cup
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3cat-cup
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4chua-thien-mu
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4chua-thien-mu
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4chua-thien-mu
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4chua-thien-mu
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4chua-thien-mu
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5ciin
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5ciin
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5ciin
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5ciin
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5ciin
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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6denisdang
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7dragon
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7dragon
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7dragon
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7dragon
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7dragon
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7dragon
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7dragon
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7dragon
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7dragon
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7dragon
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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8duck-banana
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9dug
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9dug
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9dug
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9dug
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9dug
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10elephant
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10elephant
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10elephant
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10elephant
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10elephant
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10elephant
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10elephant
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10elephant
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10elephant
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10elephant
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11fire
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11fire
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11fire
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11fire
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11fire
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11fire
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11fire
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11fire
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11fire
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11fire
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12henry
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12henry
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12henry
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12henry
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13khanhvy
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Yo'LLaVA Dataset
A dataset of 40 personalized subjects: Person (10), Pets (5), Landmarks (5), Objects (15), and Fiction Characters (5).
The dataset is divided into train and test splits. The number of images per subject varies from 10-20 images.

@inproceedings{yochameleon,
author = {Thao Nguyen and Krishna Kumar Singh and Jing Shi and Trung Bui and Yong Jae Lee and Yuheng Li},
title = {Yo\textquotesingle Chameleon: Personalized Vision and Language Generation},
year = {2025},
booktitle = {Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition (CVPR)}
}
@inproceedings{yollava,
author = {Nguyen, Thao and Liu, Haotian and Li, Yuheng and Cai, Mu and Ojha, Utkarsh and Lee, Yong Jae},
booktitle = {Advances in Neural Information Processing Systems},
title = {Yo\textquotesingle LLaVA: Your Personalized Language and Vision Assistant},
year = {2024}
}
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