title: VolDoGer: LLM-assisted Datasets for Domain Generalization in
    Vision-Language Tasks
summary: 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.
paper_authors._id: 66a8563bb8c479794409883f
paper_authors.name: Juhwan Choi
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-07-30T09:04:54.467Z
paper_authors._id: 65646b22ac9d3c2bd7b14788
paper_authors.avatarUrl: /avatars/0bf19dcfa568a694361fb3a63b999997.svg
paper_authors.fullname: Juhwan Choi
paper_authors.type: user
paper_authors.user: c-juhwan
paper_authors._id: 66a8563bb8c4797944098840
paper_authors.name: Junehyoung Kwon
paper_authors._id: 66a8563bb8c4797944098841
paper_authors.name: JungMin Yun
paper_authors._id: 66a8563bb8c4797944098842
paper_authors.name: Seunguk Yu
paper_authors._id: 66a8563bb8c4797944098843
paper_authors.name: YoungBin Kim
paper_title: VolDoGer: LLM-assisted Datasets for Domain Generalization in
    Vision-Language Tasks
paper_summary: 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.
paper_ai_keywords: domain generalizability deep learning model vision-language tasks image captioning visual question answering visual entailment vision-language dataset LLM-based data annotation multimodal large language model GroundScore