Papers by Shuichi Nishioka

1 papers
Improving Few-Shot Image Classification Using Machine- and User-Generated Natural Language Descriptions (2022.findings-naacl)

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Challenge: Humans can efficiently learn about new concepts from language descriptions, and we propose a new machine learning model, LIDE, which has a text decoder to generate the descriptions and a decoded text encoder to obtain the text representations of machine-generated descriptions.
Approach: They propose a model with a text decoder to generate the descriptions and a corresponding text encoder to obtain the text representations of machine- or user-generated descriptions.
Outcome: The proposed model outperforms baseline models with machine-generated descriptions and with high-quality user-generated models with high quality explanations.

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