Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Combining GCN and Transformer for Chinese Grammatical Error Detection   This paper describes our system at NLPTEA-2020 Task: Chinese Grammatical
Error Diagnosis (CGED). The goal of CGED is to diagnose four types of
grammatical errors: word selection (S), redundant words (R), missing words (M),
and disordered words (W). The automatic CGED system contains two parts
including error detection and error correction and our system is designed to
solve the error detection problem. Our system is built on three models: 1) a
BERT-based model leveraging syntactic information; 2) a BERT-based model
leveraging contextual embeddings; 3) a lexicon-based graph neural network
leveraging lexical information. We also design an ensemble mechanism to improve
the single model's performance. Finally, our system achieves the highest F1
scores at detection level and identification level among all teams
participating in the CGED 2020 task.

17
The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
2
The categories of this paper are: math
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat