Two methods generate parallel data for GEC, improving neural models' performance.
arXiv research
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Improved GEC models use scored data from large pretraining to outperform.
Unified framework for efficient RL in MDP, POMDP, and PSR.
The paper develops algorithms for competitive RL in partially observable MGs.
We describe an approach to Grammatical Error Correction (GEC) that is effective at making use of models trained on large amounts of weakly supervised bitext. We train the Transformer sequence-to-sequence model on 4B tokens of Wikipedia revisions and employ an iterative decoding strategy that is tailored to the loosely-…
Approximations of loopy belief propagation, including expectation propagation and approximate message passing, have attracted considerable attention for probabilistic inference problems. This paper proposes and analyzes a generalization of Opper and Winther's expectation consistent (EC) approximate inference method. Th…