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Data Troubles in Sentence Level Confidence Estimation for Machine Translation
For an English-Spanish translation model operating at $SACC = 0. 89$ according to a non-expert annotator pool we can derive a confidence estimate that labels 0. 5-0. 6 of the $good$ translations in an "in-domain" test set with 0. 95 Precision.
Practical Perspectives on Quality Estimation for Machine Translation
Sentence level quality estimation (QE) for machine translation (MT) attempts to predict the translation edit rate (TER) cost of post-editing work required to correct MT output.
SOURCE: SOURce-Conditional Elmo-style Model for Machine Translation Quality Estimation
In WMT-2019 QE task, our system ranked in the second place on En-De NMT dataset and the third place on En-Ru NMT dataset.
Dial2Desc: End-to-end Dialogue Description Generation
We first propose a new task named Dialogue Description (Dial2Desc).
A Hybrid System for Chinese Grammatical Error Diagnosis and Correction
In the correction stage, candidates were generated by the three GEC models and then merged to output the final corrections for M and S types.
Learning Energy-Based Models as Generative ConvNets via Multi-grid Modeling and Sampling
Within each iteration of our learning algorithm, for each observed training image, we generate synthesized images at multiple grids by initializing the finite-step MCMC sampling from a minimal 1 x 1 version of the training image.
