no code implementations • SemEval (NAACL) 2022 • Gaku Morio, Hiroaki Ozaki, Atsuki Yamaguchi, Yasuhiro Sogawa
In this task, we have to parse opinions considering both structure- and context-dependent subjective aspects, which is different from typical dependency parsing.
no code implementations • SemEval (NAACL) 2022 • Atsuki Yamaguchi, Gaku Morio, Hiroaki Ozaki, Yasuhiro Sogawa
In this paper, we describe our system for SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding.
1 code implementation • 11 Aug 2023 • Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi, Yasuhiro Sogawa
We rethink this and adopt a well-grounded set of deduction rules based on formal logic theory, which can derive any other deduction rules when combined in a multistep way.
1 code implementation • 18 May 2023 • Atsuki Yamaguchi, Hiroaki Ozaki, Terufumi Morishita, Gaku Morio, Yasuhiro Sogawa
Masked language modeling (MLM) is a widely used self-supervised pretraining objective, where a model needs to predict an original token that is replaced with a mask given contexts.
1 code implementation • 25 May 2022 • Terufumi Morishita, Gaku Morio, Shota Horiguchi, Hiroaki Ozaki, Nobuo Nukaga
We propose a fundamental theory on ensemble learning that answers the central question: what factors make an ensemble system good or bad?
no code implementations • 6 Dec 2021 • Atsuki Yamaguchi, Gaku Morio, Hiroaki Ozaki, Ken-ichi Yokote, Kenji Nagamatsu
This paper introduces the proposed automatic minuting system of the Hitachi team for the First Shared Task on Automatic Minuting (AutoMin-2021).
no code implementations • EACL 2021 • Hiroaki Ozaki, Gaku Morio, Terufumi Morishita, Toshinori Miyoshi
This paper describes the first report on cross-lingual transfer for semantic dependency parsing.
no code implementations • SEMEVAL 2020 • Terufumi Morishita, Gaku Morio, Hiroaki Ozaki, Toshinori Miyoshi
Due to the unsupervised nature of the task, we concentrated on inquiring about the similarity measures induced by different layers of different pre-trained Transformer-based language models, which can be good approximations of the human sense of word similarity.
no code implementations • SEMEVAL 2020 • Terufumi Morishita, Gaku Morio, Hiroaki Ozaki, Toshinori Miyoshi
Our experimental results show that SaS outperforms a naive average ensemble, leveraging weaker PLMs as well as high-performing PLMs.
no code implementations • SEMEVAL 2020 • Terufumi Morishita, Gaku Morio, Shota Horiguchi, Hiroaki Ozaki, Toshinori Miyoshi
Users of social networking services often share their emotions via multi-modal content, usually images paired with text embedded in them.
no code implementations • SEMEVAL 2020 • Gaku Morio, Terufumi Morishita, Hiroaki Ozaki, Toshinori Miyoshi
This paper shows our system for SemEval-2020 task 10, Emphasis Selection for Written Text in Visual Media.
no code implementations • SEMEVAL 2020 • Gaku Morio, Terufumi Morishita, Hiroaki Ozaki, Toshinori Miyoshi
In this paper, we show our system for SemEval-2020 task 11, where we tackle propaganda span identification (SI) and technique classification (TC).
no code implementations • CONLL 2020 • Hiroaki Ozaki, Gaku Morio, Yuta Koreeda, Terufumi Morishita, Toshinori Miyoshi
This paper presents our proposed parser for the shared task on Meaning Representation Parsing (MRP 2020) at CoNLL, where participant systems were required to parse five types of graphs in different languages.
no code implementations • ACL 2020 • Gaku Morio, Hiroaki Ozaki, Terufumi Morishita, Yuta Koreeda, Kohsuke Yanai
Our proposed model incorporates (i) task-specific parameterization (TSP) that effectively encodes a sequence of propositions and (ii) a proposition-level biaffine attention (PLBA) that can predict a non-tree argument consisting of edges.
no code implementations • LREC 2020 • Ryo Egawa, Gaku Morio, Katsuhide Fujita
To analyze persuasive strategies, it is important to understand how individuals construct posts and comments based on the semantics of the argumentative components.
no code implementations • IJCNLP 2019 • Gaku Morio, Ryo Egawa, Katsuhide Fujita
In online arguments, identifying how users construct their arguments to persuade others is important in order to understand a persuasive strategy directly.
no code implementations • CONLL 2019 • Yuta Koreeda, Gaku Morio, Terufumi Morishita, Hiroaki Ozaki, Kohsuke Yanai
This paper describes the proposed system of the Hitachi team for the Cross-Framework Meaning Representation Parsing (MRP 2019) shared task.
no code implementations • ACL 2019 • Ryo Egawa, Gaku Morio, Katsuhide Fujita
For analyzing online persuasions, one of the important goals is to semantically understand how people construct comments to persuade others.
no code implementations • WS 2018 • Gaku Morio, Katsuhide Fujita
Argument Mining (AM) is a relatively recent discipline, which concentrates on extracting claims or premises from discourses, and inferring their structures.