[PDF] Top 20 Grammatical Error Correction with Neural Reinforcement Learning
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Grammatical Error Correction with Neural Reinforcement Learning
... homophone error (there ...more grammatical by adding a possessive ...The correction by MLE looks fairly fluent as well as grammatical, but it is se- mantically ...The correction by NRL ... See full document
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Optimizing Quantum Error Correction Codes with Reinforcement Learning
... hood decoder performance over the quantum erasure channel for a given topological code (see Sec. 6.1). To simplify, we focus on the residual Z-error after cor- rection and we ignore the X -part of the ... See full document
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System Combination for Grammatical Error Correction
... of error-annotated learner (“par- allel”) ...social learning platform Lang-8 and built an SMT system for correcting grammatical errors in ...all error types are dealt ... See full document
12
Minimally Augmented Grammatical Error Correction
... Most neural approaches to automatic grammati- cal error correction (GEC) require error-labelled training data to achieve their best ... See full document
7
A Hybrid Model For Grammatical Error Correction
... A pre-processing and a post-processing filter are utilized which include filters for some idio- matic phrases extracted from the training dataset. The Frequent Pattern Growth Algorithm (FP- Growth) is widely used for ... See full document
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Generating artificial errors for grammatical error correction
... Building error correction systems using machine learning techniques can require a considerable amount of annotated data which is difficult to ob- ...Available error-annotated corpora are often ... See full document
11
Corpora Generation for Grammatical Error Correction
... Grammatical Error Correction (GEC) has been recently modeled using the sequence- to-sequence ...that neural GEC models trained using either type of corpora give similar per- ... See full document
11
A Neural Grammatical Error Correction System Built On Better Pre training and Sequential Transfer Learning
... our neural system performs well on some error cate- gories ...on error types, we found it beneficial to remove ed- its belonging to certain categories in which the model performs too ...of ... See full document
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Grammatical Error Correction with Alternating Structure Optimization
... on grammatical error correc- tion was done by Knight and Chander (1994) on arti- cle ...memory-based learning (Minnen et al., 2000), decision tree learning (Nagata et ... See full document
9
Better Evaluation for Grammatical Error Correction
... time. Grammatical error correction is an important NLP task with useful applications for second lan- guage ...for error correction is typically done by computing F 1 measure ... See full document
5
Approaching Neural Grammatical Error Correction as a Low Resource Machine Translation Task
... the error rate of NUCLE is adapted to the error rate of the original dev ...an error-rate of about ...an error-rate of 15% is ...any neural GEC system on the CoNLL ... See full document
12
Erroneous data generation for Grammatical Error Correction
... in neural Grammatical Error Correction (GEC) sys- tems can significantly improve the system ...art neural GEC system is an ensemble of four Transformer models pretrained on a large ... See full document
10
Quantum error correction for the toric code using deep reinforcement learning
... It would seem very natural to base the RL reward scheme on the success/failure information from the hid- den state. However, we found it difficult to converge to a good agent based on this, for the following reason: ... See full document
12
Neural Grammatical Error Correction Systems with Unsupervised Pre training on Synthetic Data
... synthetic error gen- eration method based on confusion sets generated from an inverted ...matical error correction ...genuine error-annotated ESL learner data is ... See full document
12
A Nested Attention Neural Hybrid Model for Grammatical Error Correction
... hybrid neural model with two nested levels of attention: word-level and ...the grammatical error correction task and achieves the best reported results on the CoNLL-14 benchmark among fully ... See full document
10
Cross Sentence Grammatical Error Correction
... Automatic grammatical error correction (GEC) research has made remarkable progress in the past ...strong neural encoder-decoder models by appropriately modeling wider ... See full document
11
Joint Learning and Inference for Grammatical Error Correction
... that grammatical er- rors interact, for various conceptual and technical reasons, this issue has not been addressed in a sig- nificant way in the ...joint learning and inference and apply it to various ... See full document
12
Neural Sequence Labelling Models for Grammatical Error Correction
... One of the first approaches to GEC as an SMT task is the one by Brockett et al. (2006), who gen- erate artificial data based on hand-crafted rules to train a model that can correct countability er- rors. Dahlmeier and Ng ... See full document
12
Neural and FST based approaches to grammatical error correction
... Stahlberg et al. (2019) demonstrated the useful- ness of FSTs for grammatical error correction. Their method starts with an input lattice I which is generated with a phrase-based statistical machine ... See full document
12
A Meta Learning Approach to Grammatical Error Correction
... for grammatical error correction with a number of small ...a grammatical error correction task for article ...different grammatical error tagged ... See full document
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