VolDoGer: LLM-assisted Datasets for Domain Generalization in
  Vision-Language Tasks
Domain generalizability is a crucial aspect of a deep learning model since it
determines the capability of the model to perform well on data from unseen
domains. However, research on the domain generalizability of deep learning
models for vision-language tasks remains limited, primarily because of the lack
of required datasets. To address these challenges, we propose VolDoGer:
Vision-Language Dataset for Domain Generalization, a dedicated dataset designed
for domain generalization that addresses three vision-language tasks: image
captioning, visual question answering, and visual entailment. We constructed
VolDoGer by extending LLM-based data annotation techniques to vision-language
tasks, thereby alleviating the burden of recruiting human annotators. We
evaluated the domain generalizability of various models, ranging from
fine-tuned models to a recent multimodal large language model, through
VolDoGer.
66a8563bb8c479794409883f
Juhwan Choi
admin_assigned
2024-07-30T09:04:54.467Z
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Juhwan Choi
user
c-juhwan
66a8563bb8c4797944098840
Junehyoung Kwon
66a8563bb8c4797944098841
JungMin Yun
66a8563bb8c4797944098842
Seunguk Yu
66a8563bb8c4797944098843
YoungBin Kim
VolDoGer: LLM-assisted Datasets for Domain Generalization in
  Vision-Language Tasks
Domain generalizability is a crucial aspect of a deep learning model since it
determines the capability of the model to perform well on data from unseen
domains. However, research on the domain generalizability of deep learning
models for vision-language tasks remains limited, primarily because of the lack
of required datasets. To address these challenges, we propose VolDoGer:
Vision-Language Dataset for Domain Generalization, a dedicated dataset designed
for domain generalization that addresses three vision-language tasks: image
captioning, visual question answering, and visual entailment. We constructed
VolDoGer by extending LLM-based data annotation techniques to vision-language
tasks, thereby alleviating the burden of recruiting human annotators. We
evaluated the domain generalizability of various models, ranging from
fine-tuned models to a recent multimodal large language model, through
VolDoGer.
A new dataset designed for evaluating domain generalization in vision-language tasks is introduced, addressing the challenge through LLM-based data annotation techniques.
VolDoGer Vision-Language Dataset for Domain Generalization image captioning visual question answering visual entailment domain generalizability fine-tuned models multimodal large language model