Sadao Kurohashi

Annotating a Driving Experience Corpus with Behavior and Subjectivity.

2018 · Institutional Repositories DataBase (IRDB)

conference paper

A System for Worldwide COVID-19 Information Aggregation

2020 · arXiv (Cornell University)

The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhile, the COVID-19 condition is very different among the …

Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning

2020

Temporal relation classification is a pair-wise task for identifying the relation of a temporal link (TLINK) between two mentions, i.e. event, time and document creation time (DCT). It leads to two crucial limits: 1) Two …

MultiTool-CoT: GPT-3 Can Use Multiple External Tools with Chain of Thought Prompting

2023 · arXiv (Cornell University)

Large language models (LLMs) have achieved impressive performance on various reasoning tasks. To further improve the performance, we propose MultiTool-CoT, a novel framework that leverages chain-of-thought (CoT) prompting to incorporate multiple external tools, such as …

EMS: Efficient and Effective Massively Multilingual Sentence Embedding Learning

2024 · IEEE/ACM Transactions on Audio Speech and Language Processing

Massively multilingual sentence representation models, e.g., LASER, SBERT-distill, and LaBSE, help significantly improve cross-lingual downstream tasks. However, the use of a large amount of data or inefficient model architectures results in heavy computation to train …

ASPEC: Asian Scientific Paper Excerpt Corpus

2016

In this paper, we describe the details of the ASPEC (Asian Scientific Paper Excerpt Corpus), which is the first large-size parallel corpus of scientific paper domain.ASPEC was constructed in the Japanese-Chinese machine translation project conducted …

An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation

2017 · arXiv (Cornell University)

In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an …

An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation

2017

In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an …

Overview of the 8th Workshop on Asian Translation

2021

Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Chenhui Chu, Akiko Eriguchi, Kaori Abe, Yusuke Oda, Sadao Kurohashi. Proceedings of …

Juman++: A Morphological Analysis Toolkit for Scriptio Continua

2018

We present a three-part toolkit for developing morphological analyzers for languages without natural word boundaries. The first part is a lattice-based morphological analysis library that uses a combination of linear and recurrent neural net language …

FAQ Retrieval using Query-Question Similarity and BERT-Based Query-Answer Relevance

2019

Frequently Asked Question (FAQ) retrieval is an important task where the objective is to retrieve an appropriate Question-Answer (QA) pair from a database based on a user's query. We propose a FAQ retrieval system that …

Overview of the 7th Workshop on Asian Translation

2020

Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Sadao Kurohashi. Proceedings of the 7th Workshop on Asian Translation. 2020.