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Makoto Morishita

7 accepted papers

2025

Long-Tail Crisis in Nearest Neighbor Language Models

NAACL 2025findings

The k-nearest-neighbor language model (kNN-LM), one of the retrieval-augmented language models, improves the perplexity for given text by directly accessing a large datastore built from any text data during inference.A widely held hypothesis for the success of kNN-LM is that its explicit memory, i.e…

2025

MQM-Chat: Multidimensional Quality Metrics for Chat Translation

COLING 2025main

The complexities of chats, such as the stylized contents specific to source segments and dialogue consistency, pose significant challenges for machine translation. Recognizing the need for a precise evaluation metric to address the issues associated with chat translation, this study introduces Multi…

2024

JaParaPat: A Large-Scale Japanese-English Parallel Patent Application Corpus

COLING 2024main

We constructed JaParaPat (Japanese-English Parallel Patent Application Corpus), a bilingual corpus of more than 300 million Japanese-English sentence pairs from patent applications published in Japan and the United States from 2000 to 2021. We obtained the publication of unexamined patent applicatio…

Cited by 2SourcePDFScholar
2024

Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMs

ACL 2024findings

In recent years, neural machine translation (NMT) has become widely used in everyday life. However, the current NMT lacks a mechanism to adjust the difficulty level of translations to match the user’s language level. Additionally, due to the bias in the training data for NMT, translations of simple…

2024

WikiSplit++: Easy Data Refinement for Split and Rephrase

COLING 2024main

The task of Split and Rephrase, which splits a complex sentence into multiple simple sentences with the same meaning, improves readability and enhances the performance of downstream tasks in natural language processing (NLP). However, while Split and Rephrase can be improved using a text-to-text gen…

2022

Domain Adaptation of Machine Translation with Crowdworkers

EMNLP 2022industry

Although a machine translation model trained with a large in-domain parallel corpus achieves remarkable results, it still works poorly when no in-domain data are available. This situation restricts the applicability of machine translation when the target domain’s data are limited. However, there is…

2020

PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents

COLING 2020main

Neural Machine Translation (NMT) has shown drastic improvement in its quality when translating clean input, such as text from the news domain. However, existing studies suggest that NMT still struggles with certain kinds of input with considerable noise, such as User-Generated Contents (UGC) on the…