2 citations · 5 across the 5 of their papers we have counts for
6 papers
Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models
Kostiantyn Omelianchuk, Andrii Liubonko, Oleksandr Skurzhanskyi +3
In this paper, we carry out experimental research on Grammatical Error Correction, delving into the nuances of single-model systems, comparing the efficiency of ensembling and rank…
Gender-Inclusive Grammatical Error Correction through Augmentation
Gunnar Lund, Kostiantyn Omelianchuk, Igor Samokhin
In this paper we show that GEC systems display gender bias related to the use of masculine and feminine terms and the gender-neutral singular "they". We develop parallel datasets o…
Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correction
Maksym Tarnavskyi, Artem Chernodub, Kostiantyn Omelianchuk
In this paper, we investigate improvements to the GEC sequence tagging architecture with a focus on ensembling of recent cutting-edge Transformer-based encoders in Large configurat…
Text Simplification by Tagging
Kostiantyn Omelianchuk, Vipul Raheja, Oleksandr Skurzhanskyi
Edit-based approaches have recently shown promising results on multiple monolingual sequence transduction tasks. In contrast to conventional sequence-to-sequence (Seq2Seq) models,…
GECToR -- Grammatical Error Correction: Tag, Not Rewrite
Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub +1
In this paper, we present a simple and efficient GEC sequence tagger using a Transformer encoder. Our system is pre-trained on synthetic data and then fine-tuned in two stages: fir…
How do you correct run-on sentences it's not as easy as it seems
Junchao Zheng, Courtney Napoles, Joel Tetreault +1
Run-on sentences are common grammatical mistakes but little research has tackled this problem to date. This work introduces two machine learning models to correct run-on sentences…