Kazumasa Omura — accepted AI-conference papers

2024

An Empirical Study of Synthetic Data Generation for Implicit Discourse Relation Recognition

Kazumasa Omura, Fei Cheng, Sadao Kurohashi

COLING 2024main

Implicit Discourse Relation Recognition (IDRR), which is the task of recognizing the semantic relation between given text spans that do not contain overt clues, is a long-standing and challenging problem. In particular, the paucity of training data for some error-prone discourse relations makes the…

Cited by 1 Source ↗PDF ↗code ↗Scholar ↗

2022

Improving Commonsense Contingent Reasoning by Pseudo-data and Its Application to the Related Tasks

Kazumasa Omura, Sadao Kurohashi

COLING 2022main

Contingent reasoning is one of the essential abilities in natural language understanding, and many language resources annotated with contingent relations have been constructed. However, despite the recent advances in deep learning, the task of contingent reasoning is still difficult for computers. I…

Cited by 6 Source ↗PDF ↗code ↗Scholar ↗