Papers by Simon Flachs
Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses (2020.emnlp-main)
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| Challenge: | CWEB is a new benchmark for grammatical error correction (GEC) systems . website data contains far fewer grammamatical errors than learner essays . |
| Approach: | They propose to broaden the target domain of grammatical error correction (GEC) systems . website data contains far fewer grammamatical errors than learner essays . |
| Outcome: | The proposed model can't rely on a strong internal language model in low error density domains. |
A Simple and Robust Approach to Detecting Subject-Verb Agreement Errors (N19-1)
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| Challenge: | a recent study shows that neural sequential labelers overfit their training data to detect SVA errors. |
| Approach: | They propose a simple protocol that generates a neural sequential labeler from silver standard data and gold standard data. |
| Outcome: | The proposed method leads to more robust detection of SVA errors on silver standard data and gold standard data. |
Historical Text Normalization with Delayed Rewards (P19-1)
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| Challenge: | Recent work on a novel approach to historical text normalization has shown that policy gradient fine-tuning improves accuracy across languages. |
| Approach: | They propose to train sequence-to-sequence models with simple token-level log-likelihood with reinforcement learning to optimize for exact matches. |
| Outcome: | The proposed model outperforms phrase-based models in the evaluation metric for historical text normalization across languages. |