Papers by Kohsuke Yanai

2 papers
Towards Better Non-Tree Argument Mining: Proposition-Level Biaffine Parsing with Task-Specific Parameterization (2020.acl-main)

Copied to clipboard

Challenge: Argument mining studies have advanced the ability to predict argument structures, but the technology for capturing non-tree-structured arguments is still in its infancy.
Approach: They propose a neural model that can predict proposition types and edges between propositions.
Outcome: The proposed model improves edge prediction performance compared to baseline models.
End-to-end Argument Mining with Cross-corpora Multi-task Learning (2022.tacl-1)

Copied to clipboard

Challenge: Argument(ation) mining is a task of identifying argument structure from text . lack of training data makes it difficult to train models based on limited data sets.
Approach: They propose an end-to-end cross-corpus argument mining method that uses auxiliary argument mining corpora to train models.
Outcome: The proposed method outperforms models trained on a single corpus on arguments on arguments in argument mining tasks.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations