activity
20172023
most citedInterpretable Adversarial Perturbation in Input Embedding Space for Text

37 citations · 122 across the 29 of their papers we have counts for

collaborators

30 papers

cs.CL2023★ 3 cited

Chat Translation Error Detection for Assisting Cross-lingual Communications

Yunmeng Li, Jun Suzuki, Makoto Morishita +4

In this paper, we describe the development of a communication support system that detects erroneous translations to facilitate crosslingual communications due to the limitations of…

quant-ph2023

Error tradeoff relation for estimating the unitary-shift parameter of a relativistic spin-1/2 particle

Shin Funada, Jun Suzuki

The purpose of this paper is to discuss the existence of a nontrivial tradeoff relation for estimating two unitary-shift parameters in a relativistic spin-1/2 system. It is shown t…

quant-ph2023

Bayesian Nagaoka-Hayashi Bound for Multiparameter Quantum-State Estimation Problem

Jun Suzuki

In this work we propose a Bayesian version of the Nagaoka-Hayashi bound when estimating a parametric family of quantum states. This lower bound is a generalization of a recently pr…

cs.CL2022★ 1 cited

Bipartite-play Dialogue Collection for Practical Automatic Evaluation of Dialogue Systems

Shiki Sato, Yosuke Kishinami, Hiroaki Sugiyama +3

Automation of dialogue system evaluation is a driving force for the efficient development of dialogue systems. This paper introduces the bipartite-play method, a dialogue collectio…

cs.CL2022

Domain Adaptation of Machine Translation with Crowdworkers

Makoto Morishita, Jun Suzuki, Masaaki Nagata

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 si…

cs.CL2022★ 8 cited

Target-Guided Open-Domain Conversation Planning

Yosuke Kishinami, Reina Akama, Shiki Sato +3

Prior studies addressing target-oriented conversational tasks lack a crucial notion that has been intensively studied in the context of goal-oriented artificial intelligence agents…