1 citations · 1 across the 4 of their papers we have counts for
4 papers
Quantifying Lexical Semantic Shift via Unbalanced Optimal Transport
Ryo Kishino, Hiroaki Yamagiwa, Ryo Nagata +2
Lexical semantic change detection aims to identify shifts in word meanings over time. While existing methods using embeddings from a diachronic corpus pair estimate the degree of c…
Contextualized Word Vector-based Methods for Discovering Semantic Differences with No Training nor Word Alignment
Ryo Nagata, Hiroya Takamura, Naoki Otani +1
In this paper, we propose methods for discovering semantic differences in words appearing in two corpora based on the norms of contextualized word vectors. The key idea is that the…
Exploring the Capacity of a Large-scale Masked Language Model to Recognize Grammatical Errors
Ryo Nagata, Manabu Kimura, Kazuaki Hanawa
In this paper, we explore the capacity of a language model-based method for grammatical error detection in detail. We first show that 5 to 10% of training data are enough for a BER…
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?
Masato Mita, Tomoya Mizumoto, Masahiro Kaneko +2
This study explores the necessity of performing cross-corpora evaluation for grammatical error correction (GEC) models. GEC models have been previously evaluated based on a single…