Context is Key: Grammatical Error Detection with Contextual Word Representations

15 June 2019

Papers citing "Context is Key: Grammatical Error Detection with Contextual Word Representations"

10 / 10 papers shown

Title
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations Hadas Orgad Michael Toker Zorik Gekhman Roi Reichart Idan Szpektor Hadas Kotek Yonatan Belinkov HILM AIFin 61 32 0 03 Oct 2024
Oddballness: universal anomaly detection with language models Filip Graliñski Ryszard Staruch Krzysztof Jurkiewicz 37 1 0 04 Sep 2024
Grammatical Error Correction: A Survey of the State of the Art Christopher Bryant Zheng Yuan Muhammad Reza Qorib Hannan Cao Hwee Tou Ng Ted Briscoe 3DV 34 79 0 09 Nov 2022
Plug-Tagger: A Pluggable Sequence Labeling Framework Using Language Models Xin Zhou Ruotian Ma Tao Gui Y. Tan Qi Zhang Xuanjing Huang VLM 18 5 0 14 Oct 2021
Combining GCN and Transformer for Chinese Grammatical Error Detection Jinhong Zhang 29 6 0 19 May 2021
Improving BERT with Syntax-aware Local Attention Zhongli Li Qingyu Zhou Chao Li Ke Xu Yunbo Cao 63 44 0 30 Dec 2020
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction Masahiro Kaneko Masato Mita Shun Kiyono Jun Suzuki Kentaro Inui 35 143 0 03 May 2020
Detecting Local Insights from Global Labels: Supervised & Zero-Shot Sequence Labeling via a Convolutional Decomposition A. Schmaltz 27 8 0 04 Jun 2019
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task Marcin Junczys-Dowmunt Roman Grundkiewicz Shubha Guha Kenneth Heafield 33 192 0 16 Apr 2018
Attending to Characters in Neural Sequence Labeling Models Marek Rei Gamal K. O. Crichton S. Pyysalo 49 187 0 14 Nov 2016