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Found 2 papers, 2 papers with code
Learning from Rules Generalizing Labeled Exemplars
Empirical evaluation on five different tasks shows that (1) our algorithm is more accurate than several existing methods of learning from a mix of clean and noisy supervision, and (2) the coupled rule-exemplar supervision is effective in denoising rules.
Parallel Iterative Edit Models for Local Sequence Transduction
We present a Parallel Iterative Edit (PIE) model for the problem of local sequence transduction arising in tasks like Grammatical error correction (GEC).
Ranked #13 on
Grammatical Error Correction
on CoNLL-2014 Shared Task
Grammatical Error Correction
Optical Character Recognition (OCR)
