Search Results for author: Daisuke Kawahara

Found 65 papers, 9 papers with code

JGLUE: Japanese General Language Understanding Evaluation

2 code implementations LREC 2022 Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata

We build a Japanese NLU benchmark, JGLUE, from scratch without translation to measure the general NLU ability in Japanese.

FLUE Natural Language Understanding +1

A Method for Building a Commonsense Inference Dataset based on Basic Events

no code implementations EMNLP 2020 Kazumasa Omura, Daisuke Kawahara, Sadao Kurohashi

We present a scalable, low-bias, and low-cost method for building a commonsense inference dataset that combines automatic extraction from a corpus and crowdsourcing.

Multiple-choice Transfer Learning

Should We Respect LLMs? A Cross-Lingual Study on the Influence of Prompt Politeness on LLM Performance

no code implementations22 Feb 2024 Ziqi Yin, Hao Wang, Kaito Horio, Daisuke Kawahara, Satoshi Sekine

We investigate the impact of politeness levels in prompts on the performance of large language models (LLMs).

SlideAVSR: A Dataset of Paper Explanation Videos for Audio-Visual Speech Recognition

no code implementations18 Jan 2024 Hao Wang, Shuhei Kurita, Shuichiro Shimizu, Daisuke Kawahara

Audio-visual speech recognition (AVSR) is a multimodal extension of automatic speech recognition (ASR), using video as a complement to audio.

Audio-Visual Speech Recognition Automatic Speech Recognition +4

PHALM: Building a Knowledge Graph from Scratch by Prompting Humans and a Language Model

1 code implementation11 Oct 2023 Tatsuya Ide, Eiki Murata, Daisuke Kawahara, Takato Yamazaki, Shengzhe Li, Kenta Shinzato, Toshinori Sato

In this paper, we propose PHALM, a method of building a knowledge graph from scratch, by prompting both crowdworkers and a large language model (LLM).

Language Modelling Large Language Model +1

Grounding in social media: An approach to building a chit-chat dialogue model

no code implementations NAACL (ACL) 2022 Ritvik Choudhary, Daisuke Kawahara

Building open-domain dialogue systems capable of rich human-like conversational ability is one of the fundamental challenges in language generation.

Dialogue Generation

Generate, Evaluate, and Select: A Dialogue System with a Response Evaluator for Diversity-Aware Response Generation

no code implementations NAACL (ACL) 2022 Ryoma Sakaeda, Daisuke Kawahara

We aim to overcome the lack of diversity in responses of current dialogue systems and to develop a dialogue system that is engaging as a conversational partner.

Response Generation

Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions

1 code implementation ACL 2022 Tatsuya Ide, Daisuke Kawahara

We hope that the constructed corpus will facilitate the study on emotion recognition in a dialogue and emotion-aware dialogue response generation.

Emotion Recognition Multi-Task Learning +1

BERT-based Cohesion Analysis of Japanese Texts

1 code implementation COLING 2020 Nobuhiro Ueda, Daisuke Kawahara, Sadao Kurohashi

The meaning of natural language text is supported by cohesion among various kinds of entities, including coreference relations, predicate-argument structures, and bridging anaphora relations.


Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction

1 code implementation Findings of the Association for Computational Linguistics 2020 Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi

We propose a novel Sequence-to-Unordered-Multi-Tree (Seq2UMTree) model to minimize the effects of exposure bias by limiting the decoding length to three within a triplet and removing the order among triplets.

Joint Entity and Relation Extraction Relation

Building a Japanese Typo Dataset from Wikipedia's Revision History

no code implementations ACL 2020 Yu Tanaka, Yugo Murawaki, Daisuke Kawahara, Sadao Kurohashi

User generated texts contain many typos for which correction is necessary for NLP systems to work.

Acquiring Social Knowledge about Personality and Driving-related Behavior

no code implementations LREC 2020 Ritsuko Iwai, Daisuke Kawahara, Takatsune Kumada, Sadao Kurohashi

Using them, we automatically extracted collocations between personality descriptors and driving-related behavior from a driving behavior and subjectivity corpus (1, 803, 328 sentences after filtering) and obtained unique 5, 334 collocations.

Development of a Japanese Personality Dictionary based on Psychological Methods

no code implementations LREC 2020 Ritsuko Iwai, Daisuke Kawahara, Takatsune Kumada, Sadao Kurohashi

In this study, we collect personality words, using word embeddings, and construct a personality dictionary with weights for Big Five traits.

Word Embeddings

Tree-structured Decoding for Solving Math Word Problems

no code implementations IJCNLP 2019 Qianying Liu, Wenyv Guan, Sujian Li, Daisuke Kawahara

To address this problem, we propose a tree-structured decoding method that generates the abstract syntax tree of the equation in a top-down manner.


Machine Comprehension Improves Domain-Specific Japanese Predicate-Argument Structure Analysis

no code implementations WS 2019 Norio Takahashi, Tomohide Shibata, Daisuke Kawahara, Sadao Kurohashi

To improve the accuracy of predicate-argument structure (PAS) analysis, large-scale training data and knowledge for PAS analysis are indispensable.

Reading Comprehension

Juman++: A Morphological Analysis Toolkit for Scriptio Continua

1 code implementation EMNLP 2018 Arseny Tolmachev, Daisuke Kawahara, Sadao Kurohashi

We present a three-part toolkit for developing morphological analyzers for languages without natural word boundaries.

Art Analysis Language Modelling +2

Neural Adversarial Training for Semi-supervised Japanese Predicate-argument Structure Analysis

no code implementations ACL 2018 Shuhei Kurita, Daisuke Kawahara, Sadao Kurohashi

Japanese predicate-argument structure (PAS) analysis involves zero anaphora resolution, which is notoriously difficult.

Consistent Word Segmentation, Part-of-Speech Tagging and Dependency Labelling Annotation for Chinese Language

no code implementations COLING 2016 Mo Shen, Wingmui Li, HyunJeong Choe, Chenhui Chu, Daisuke Kawahara, Sadao Kurohashi

In this paper, we propose a new annotation approach to Chinese word segmentation, part-of-speech (POS) tagging and dependency labelling that aims to overcome the two major issues in traditional morphology-based annotation: Inconsistency and data sparsity.

Chinese Word Segmentation Machine Translation +6

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