Jun Suzuki

Enumeration of Extractive Oracle Summaries

2017

To analyze the limitations and the future directions of the extractive summarization paradigm, this paper proposes an Integer Linear Programming (ILP) formulation to obtain extractive oracle summaries in terms of ROUGE n . We also …

An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction

2019 · arXiv (Cornell University)

The incorporation of pseudo data in the training of grammatical error correction models has been one of the main factors in improving the performance of such models. However, consensus is lacking on experimental configurations, namely, …

Quantum state estimation with nuisance parameters

2020 · Journal of Physics A Mathematical and Theoretical

Abstract In parameter estimation, nuisance parameters refer to parameters that are not of interest but nevertheless affect the precision of estimating other parameters of interest. For instance, the strength of noises in a probe can …

Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese

2020

We examine a methodology using neural language models (LMs) for analyzing the word order of language. This LM-based method has the potential to overcome the difficulties existing methods face, such as the propagation of preprocessor …

A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction

2020 · arXiv (Cornell University)

Existing approaches for grammatical error correction (GEC) largely rely on supervised learning with manually created GEC datasets. However, there has been little focus on verifying and ensuring the quality of the datasets, and on how …

Domain Adaptation of Machine Translation with Crowdworkers

2022 · arXiv (Cornell University)

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 …

Neural Headline Generation on Abstract Meaning Representation

2016

Neural network-based encoder-decoder models are among recent attractive methodologies for tackling natural language generation tasks. This paper investigates the usefulness of structural syntactic and semantic information additionally incorporated in a baseline neural attention-based model. We …

Effective Adversarial Regularization for Neural Machine Translation

2019

A regularization technique based on adversarial perturbation, which was initially developed in the field of image processing, has been successfully applied to text classification tasks and has yielded attractive improvements. We aim to further leverage …