1 citations · 2 across the 5 of their papers we have counts for
5 papers
On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons
Takeshi Kojima, Itsuki Okimura, Yusuke Iwasawa +2
Current decoder-based pre-trained language models (PLMs) successfully demonstrate multilingual capabilities. However, it is unclear how these models handle multilingualism. We anal…
Analyzing Syntactic Generalization Capacity of Pre-trained Language Models on Japanese Honorific Conversion
Ryo Sekizawa, Hitomi Yanaka
Using Japanese honorifics is challenging because it requires not only knowledge of the grammatical rules but also contextual information, such as social relationships. It remains u…
Does Character-level Information Always Improve DRS-based Semantic Parsing?
Tomoya Kurosawa, Hitomi Yanaka
Even in the era of massive language models, it has been suggested that character-level representations improve the performance of neural models. The state-of-the-art neural semanti…
Is Japanese CCGBank empirically correct? A case study of passive and causative constructions
Daisuke Bekki, Hitomi Yanaka
The Japanese CCGBank serves as training and evaluation data for developing Japanese CCG parsers. However, since it is automatically generated from the Kyoto Corpus, a dependency tr…
Compositional Evaluation on Japanese Textual Entailment and Similarity
Hitomi Yanaka, Koji Mineshima
Natural Language Inference (NLI) and Semantic Textual Similarity (STS) are widely used benchmark tasks for compositional evaluation of pre-trained language models. Despite growing…