4 citations · 5 across the 6 of their papers we have counts for
9 papers
Instance-Based Neural Dependency Parsing
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi +4
Interpretable rationales for model predictions are crucial in practical applications. We develop neural models that possess an interpretable inference process for dependency parsin…
Incorporating Residual and Normalization Layers into Analysis of Masked Language Models
Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi +1
Transformer architecture has become ubiquitous in the natural language processing field. To interpret the Transformer-based models, their attention patterns have been extensively a…
Modeling Event Salience in Narratives via Barthes' Cardinal Functions
Takaki Otake, Sho Yokoi, Naoya Inoue +3
Events in a narrative differ in salience: some are more important to the story than others. Estimating event salience is useful for tasks such as story generation, and as a tool fo…
Langsmith: An Interactive Academic Text Revision System
Takumi Ito, Tatsuki Kuribayashi, Masatoshi Hidaka +2
Despite the current diversity and inclusion initiatives in the academic community, researchers with a non-native command of English still face significant obstacles when writing pa…
Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese
Tatsuki Kuribayashi, Takumi Ito, Jun Suzuki +1
We examine a methodology using neural language models (LMs) for analyzing the word order of language. This LM-based method has the potential to overcome the difficulties existing m…
Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi +4
Interpretable rationales for model predictions play a critical role in practical applications. In this study, we develop models possessing interpretable inference process for struc…