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 …

Grammatical error correction (GEC) is an important application aspect of natural language
processing techniques, and GEC system is a kind of very important intelligent system that …

Earthquake signal detection and seismic phase picking are challenging tasks in the
processing of noisy data and the monitoring of microearthquakes. Here we present a global …

First derived from human intuition, later adapted to machine translation for automatic token
alignment, attention mechanism, a simple method that can be used for encoding sequence …

Neural machine translation systems have become state-of-the-art approaches for
Grammatical Error Correction (GEC) task. In this paper, we propose a copy-augmented …

Chinese spelling correction (CSC) is a task to detect and correct spelling errors in texts. CSC
is essentially a linguistic problem, thus the ability of language understanding is crucial to this …

We improve automatic correction of grammatical, orthographic, and collocation errors in text
using a multilayer convolutional encoder-decoder neural network. The network is initialized …

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 …

We present a Parallel Iterative Edit (PIE) model for the problem of local sequence
transduction arising in tasks like Grammatical error correction (GEC). Recent approaches …

Previously, neural methods in grammatical error correction (GEC) did not reach state-of-the-
art results compared to phrase-based statistical machine translation (SMT) baselines. We …