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Fig. 1 | EURASIP Journal on Wireless Communications and Networking

Fig. 1

From: A multi-task learning framework for efficient grammatical error correction of textual messages in mobile communications

Fig. 1

The architecture of our model. The input sentence is first checked to be incorrect by the Discriminator, then located errors’ positions by the Detector, and finally corrected by the Corrector. Two errors are detected and the maximum correction length M is set to 3 in this example. N/A refers to any token as it occurs after token ‘[EOP]’

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