4 papers
Synth-JDoc: Synthesizing a Japanese Document Image Dataset for OCR with Diverse Layouts and Embedded Images
Keito Sasagawa, Shuhei Kurita, Daisuke Kawahara
The ability of Large Vision Language Models (LVLMs) to read text within document images is crucial, as it enables various applications such as Document Visual Question Answering. T…
Jagle: Building a Large-Scale Japanese Multimodal Post-Training Dataset for Vision-Language Models
Issa Sugiura, Keito Sasagawa, Keisuke Nakao +8
Developing vision-language models (VLMs) that generalize across diverse tasks requires large-scale training datasets with diverse content. In English, such datasets are typically c…
Evaluating Multimodal Large Language Models on Vertically Written Japanese Text
Keito Sasagawa, Shuhei Kurita, Daisuke Kawahara
Multimodal Large Language Models (MLLMs) have seen rapid advances in recent years and are now being applied to visual document understanding tasks. They are expected to process a w…
Constructing Multimodal Datasets from Scratch for Rapid Development of a Japanese Visual Language Model
Keito Sasagawa, Koki Maeda, Issa Sugiura +3
To develop high-performing Visual Language Models (VLMs), it is essential to prepare multimodal resources, such as image-text pairs, interleaved data, and instruction data. While m…