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20162022
most citedA Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction

97 citations · 137 across the 13 of their papers we have counts for

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20 papers · 1 filter

cs.CL2022

Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation

Qingyu Tan, Ruidan He, Lidong Bing +1

Document-level Relation Extraction (DocRE) is a more challenging task compared to its sentence-level counterpart. It aims to extract relations from multiple sentences at once. In t…

cs.CL2022

A Semi-supervised Learning Approach with Two Teachers to Improve Breakdown Identification in Dialogues

Qian Lin, Hwee Tou Ng

Identifying breakdowns in ongoing dialogues helps to improve communication effectiveness. Most prior work on this topic relies on human annotated data and data augmentation to lear…

cs.CL2021

System Combination for Grammatical Error Correction Based on Integer Programming

Ruixi Lin, Hwee Tou Ng

In this paper, we propose a system combination method for grammatical error correction (GEC), based on nonlinear integer programming (IP). Our method optimizes a novel F score obje…

cs.CL20213 cited

Diversity-Driven Combination for Grammatical Error Correction

Wenjuan Han, Hwee Tou Ng

Grammatical error correction (GEC) is the task of detecting and correcting errors in a written text. The idea of combining multiple system outputs has been successfully used in GEC…

cs.CL202115 cited

Translating from Morphologically Complex Languages: A Paraphrase-Based Approach

Preslav Nakov, Hwee Tou Ng

We propose a novel approach to translating from a morphologically complex language. Unlike previous research, which has targeted word inflections and concatenations, we focus on th…

cs.CL20211 cited

A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents

Tapas Nayak, Hwee Tou Ng

Distantly supervised datasets for relation extraction mostly focus on sentence-level extraction, and they cover very few relations. In this work, we propose cross-document relation…