1 code implementation • 2 Oct 2023 • Atsuki Yamaguchi, Terufumi Morishita
We present appjsonify, a Python-based PDF-to-JSON conversion toolkit for academic papers.
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 • 6 Aug 2023 • Yuta Koreeda, Terufumi Morishita, Osamu Imaichi, Yasuhiro Sogawa
Writing a readme is a crucial aspect of software development as it plays a vital role in managing and reusing program code.
1 code implementation • 16 Jun 2023 • Takuro Fujii, Koki Shibata, Atsuki Yamaguchi, Terufumi Morishita, Yasuhiro Sogawa
This paper investigates the effect of tokenizers on the downstream performance of pretrained language models (PLMs) in scriptio continua languages where no explicit spaces exist between words, using Japanese as a case study.
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 • 19 Apr 2023 • Yuichi Sasazawa, Terufumi Morishita, Hiroaki Ozaki, Osamu Imaichi, Yasuhiro Sogawa
In this paper, we tackle a novel task of controlling not only keywords but also the position of each keyword in the text generation.
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 • 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 • 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.