Grammatical error correction: A survey of the state of the art
Abstract Grammatical Error Correction (GEC) is the task of automatically detecting and
correcting errors in text. The task not only includes the correction of grammatical errors, such …
correcting errors in text. The task not only includes the correction of grammatical errors, such …
Neural approaches to conversational AI
This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …
few years. We group conversational systems into three categories:(1) question answering …
Findings of the 2017 conference on machine translation (wmt17)
This paper presents the results of the WMT17 shared tasks, which included three machine
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …
How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
We investigate evaluation metrics for dialogue response generation systems where
supervised labels, such as task completion, are not available. Recent works in response …
supervised labels, such as task completion, are not available. Recent works in response …
A knowledge-grounded neural conversation model
M Ghazvininejad, C Brockett, MW Chang… - Proceedings of the …, 2018 - ojs.aaai.org
Neural network models are capable of generating extremely natural sounding
conversational interactions. However, these models have been mostly applied to casual …
conversational interactions. However, these models have been mostly applied to casual …
Fully character-level neural machine translation without explicit segmentation
Most existing machine translation systems operate at the level of words, relying on explicit
segmentation to extract tokens. We introduce a neural machine translation (NMT) model that …
segmentation to extract tokens. We introduce a neural machine translation (NMT) model that …
Results of the WMT20 metrics shared task
This paper presents the results of the WMT20 Metrics Shared Task. Participants were asked
to score the outputs of the translation systems competing in the WMT20 News Translation …
to score the outputs of the translation systems competing in the WMT20 News Translation …
Results of the WMT19 metrics shared task: Segment-level and strong MT systems pose big challenges
This paper presents the results of the WMT19 Metrics Shared Task. Participants were asked
to score the outputs of the translations systems competing in the WMT19 News Translation …
to score the outputs of the translations systems competing in the WMT19 News Translation …
Attaining the unattainable? reassessing claims of human parity in neural machine translation
We reassess a recent study (Hassan et al., 2018) that claimed that machine translation (MT)
has reached human parity for the translation of news from Chinese into English, using …
has reached human parity for the translation of news from Chinese into English, using …
Unsupervised quality estimation for neural machine translation
Quality Estimation (QE) is an important component in making Machine Translation (MT)
useful in real-world applications, as it is aimed to inform the user on the quality of the MT …
useful in real-world applications, as it is aimed to inform the user on the quality of the MT …