KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media
원문 초록
In this paper, we describe our approach to utilize pre-trained BERT models with Convolutional Neural Networks for sub-task A of the Multilingual Offensive Language Identification shared task (OffensEval 2020), which is a part of the SemEval 2020. We show that combining CNN with BERT is better than using BERT on its own, and we emphasize the importance of utilizing pre-trained language models for downstream tasks. Our system, ranked 4th with macro averaged F1-Score of 0.897 in Arabic, 4th with score of 0.843 in Greek, and 3rd with score of 0.814 in Turkish. Additionally, we present ArabicBERT, a set of pre-trained transformer language models for Arabic that we share with the community.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification
CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training
Advancing Uto-Aztecan Language Technologies: A Case Study on the Endangered Comanche Language
KréyoLID From Language Identification Towards Language Mining
English Please: Evaluating Machine Translation with Large Language Models for Multilingual Bug Reports
Multi-label Scandinavian Language Identification (SLIDE)
토론
이 논문과 연결된 포럼 글이 아직 없습니다.