9 citations · 19 across the 9 of their papers we have counts for
9 papers
MQM-Chat: Multidimensional Quality Metrics for Chat Translation
Yunmeng Li, Jun Suzuki, Makoto Morishita +2
The complexities of chats pose significant challenges for machine translation models. Recognizing the need for a precise evaluation metric to address the issues of chat translation…
An Investigation of Warning Erroneous Chat Translations in Cross-lingual Communication
Yunmeng Li, Jun Suzuki, Makoto Morishita +2
Machine translation models are still inappropriate for translating chats, despite the popularity of translation software and plug-in applications. The complexity of dialogues poses…
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…
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents
Ryo Fujii, Masato Mita, Kaori Abe +4
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 tha…
Embeddings of Label Components for Sequence Labeling: A Case Study of Fine-grained Named Entity Recognition
Takuma Kato, Kaori Abe, Hiroki Ouchi +3
In general, the labels used in sequence labeling consist of different types of elements. For example, IOB-format entity labels, such as B-Person and I-Person, can be decomposed int…
cvpaper.challenge in 2016: Futuristic Computer Vision through 1,600 Papers Survey
Hirokatsu Kataoka, Soma Shirakabe, Yun He +14
The paper gives futuristic challenges disscussed in the cvpaper.challenge. In 2015 and 2016, we thoroughly study 1,600+ papers in several conferences/journals such as CVPR/ICCV/ECC…
Collaborative Descriptors: Convolutional Maps for Preprocessing
Hirokatsu Kataoka, Kaori Abe, Akio Nakamura +1
The paper presents a novel concept for collaborative descriptors between deeply learned and hand-crafted features. To achieve this concept, we apply convolutional maps for pre-proc…
Changing Fashion Cultures
Kaori Abe, Teppei Suzuki, Shunya Ueta +3
The paper presents a novel concept that analyzes and visualizes worldwide fashion trends. Our goal is to reveal cutting-edge fashion trends without displaying an ordinary fashion s…
cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey
Hirokatsu Kataoka, Yudai Miyashita, Tomoaki Yamabe +9
The "cvpaper.challenge" is a group composed of members from AIST, Tokyo Denki Univ. (TDU), and Univ. of Tsukuba that aims to systematically summarize papers on computer vision, pat…