15 citations · 21 across the 6 of their papers we have counts for
6 papers
A Highly Clean Recipe Dataset with Ingredient States Annotation for State Probing Task
Mashiro Toyooka, Kiyoharu Aizawa, Yoko Yamakata
Large Language Models (LLMs) are trained on a vast amount of procedural texts, but they do not directly observe real-world phenomena. In the context of cooking recipes, this poses…
World Food Atlas Project
Ali Rostami, Z Xie, A Ishino +3
A coronavirus pandemic is forcing people to be "at home" all over the world. In a life of hardly ever going out, we would have realized how the food we eat affects our bodies. What…
FoodMLLM-JP: Leveraging Multimodal Large Language Models for Japanese Recipe Generation
Yuki Imajuku, Yoko Yamakata, Kiyoharu Aizawa
Research on food image understanding using recipe data has been a long-standing focus due to the diversity and complexity of the data. Moreover, food is inextricably linked to peop…
An experimental framework for designing document structure for users' decision making -- An empirical study of recipes
Rina Kagawa, Masaki Matsubara, Rei Miyata +3
Textual documents need to be of good quality to ensure effective asynchronous communication in remote areas, especially during the COVID-19 pandemic. However, defining a preferred…
Noisy Annotation Refinement for Object Detection
Jiafeng Mao, Qing Yu, Yoko Yamakata +1
Supervised training of object detectors requires well-annotated large-scale datasets, whose production is costly. Therefore, some efforts have been made to obtain annotations in ec…
Recognition of Multiple Food Items in a Single Photo for Use in a Buffet-Style Restaurant
Masashi Anzawa, Sosuke Amano, Yoko Yamakata +3
We investigate image recognition of multiple food items in a single photo, focusing on a buffet restaurant application, where menu changes at every meal, and only a few images per…