no code implementations • 18 Jun 2024 • Irfan Robbani, Paul Reisert, Naoya Inoue, Surawat Pothong, Camélia Guerraoui, Wenzhi Wang, Shoichi Naito, Jungmin Choi, Kentaro Inui
Prior research in computational argumentation has mainly focused on scoring the quality of arguments, with less attention on explicating logical errors.
no code implementations • 18 Feb 2024 • Zining Wang, Paul Reisert, Eric Nichols, Randy Gomez
We develop a custom, state-of-the-art emotion recognition model to dynamically select the robot's tone of voice and utilize emojis from LLM output as cues for generating robot actions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • 28 Jul 2023 • Camélia Guerraoui, Paul Reisert, Naoya Inoue, Farjana Sultana Mim, Shoichi Naito, Jungmin Choi, Irfan Robbani, Wenzhi Wang, Kentaro Inui
The use of argumentation in education has been shown to improve critical thinking skills for end-users such as students, and computational models for argumentation have been developed to assist in this process.
no code implementations • 16 Apr 2021 • Keshav Singh, Paul Reisert, Naoya Inoue, Kentaro Inui
We construct a preliminary dataset of 6, 000 warrants annotated over 600 arguments for 3 debatable topics.
no code implementations • 13 Oct 2020 • Farjana Sultana Mim, Naoya Inoue, Paul Reisert, Hiroki Ouchi, Kentaro Inui
Existing approaches for automated essay scoring and document representation learning typically rely on discourse parsers to incorporate discourse structure into text representation.
no code implementations • WS 2019 • Pride Kavumba, Naoya Inoue, Benjamin Heinzerling, Keshav Singh, Paul Reisert, Kentaro Inui
Pretrained language models, such as BERT and RoBERTa, have shown large improvements in the commonsense reasoning benchmark COPA.
no code implementations • WS 2019 • Keshav Singh, Paul Reisert, Naoya Inoue, Pride Kavumba, Kentaro Inui
Recognizing the implicit link between a claim and a piece of evidence (i. e. warrant) is the key to improving the performance of evidence detection.
no code implementations • 8 Oct 2019 • Paul Reisert, Benjamin Heinzerling, Naoya Inoue, Shun Kiyono, Kentaro Inui
Counter-arguments (CAs), one form of constructive feedback, have been proven to be useful for critical thinking skills.
no code implementations • WS 2019 • Tomoya Mizumoto, Hiroki Ouchi, Yoriko Isobe, Paul Reisert, Ryo Nagata, Satoshi Sekine, Kentaro Inui
This paper provides an analytical assessment of student short answer responses with a view to potential benefits in pedagogical contexts.
no code implementations • ACL 2019 • Tatsuki Kuribayashi, Hiroki Ouchi, Naoya Inoue, Paul Reisert, Toshinori Miyoshi, Jun Suzuki, Kentaro Inui
For several natural language processing (NLP) tasks, span representation design is attracting considerable attention as a promising new technique; a common basis for an effective design has been established.
1 code implementation • ACL 2019 • Farjana Sultana Mim, Naoya Inoue, Paul Reisert, Hiroki Ouchi, Kentaro Inui
Existing document embedding approaches mainly focus on capturing sequences of words in documents.
no code implementations • WS 2019 • Qin Dai, Naoya Inoue, Paul Reisert, Ryo Takahashi, Kentaro Inui
In this work, we firstly investigate the feasibility of this framework on scientific dataset, specifically on biomedical dataset.
1 code implementation • WS 2018 • Paul Reisert, Naoya Inoue, Tatsuki Kuribayashi, Kentaro Inui
Most of the existing works on argument mining cast the problem of argumentative structure identification as classification tasks (e. g. attack-support relations, stance, explicit premise/claim).
no code implementations • 7 Dec 2017 • Paul Reisert, Naoya Inoue, Naoaki Okazaki, Kentaro Inui
Our coverage result of 74. 6% indicates that argumentative relations can reasonably be explained by our small pattern set.