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Abusive Language
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/advaithavetagiri/cnlp-nits-pp
공식 코드https://github.com/afrihate/afrihate
공식 코드https://github.com/amandacurry/convabuse
공식 코드ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AI
https://github.com/befittingcrown/ekohate
공식 코드https://github.com/callmesanfornow/fsl-audio-abuse
공식 코드Towards Cross-Lingual Audio Abuse Detection in Low-Resource Settings with Few-Shot Learning
https://github.com/cthem/hate-speech-detection
공식 코드https://github.com/db758/icwsm_data_challenge
공식 코드Examining Racial Bias in an Online Abuse Corpus with Structural Topic Modeling
https://github.com/dhfbk/twitter-abusive-context-dataset
공식 코드https://github.com/ewsheng/ad-hom-in-dialogue
공식 코드"Nice Try, Kiddo": Investigating Ad Hominems in Dialogue Responses
https://github.com/fgaim/tigrinya-abusive-language-detection
공식 코드A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
https://github.com/ghzhang233/Non-Discrimination-Learning-for-Text-Classification
공식 코드https://github.com/hannahkirk/activetransformers-for-abusivelanguage
공식 코드https://github.com/hate-alert/indicabusive
공식 코드Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages
https://github.com/hate-alert/urduabuseandthreat
공식 코드https://github.com/isarnejad/global-sufficiency
공식 코드https://github.com/isarnejad/tcav-for-text-classifiers
공식 코드Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors
https://github.com/jaeyk/intersectional-bias-in-ml
공식 코드Intersectional Bias in Hate Speech and Abusive Language Datasets
https://github.com/palomapiot/distil-metahate
공식 코드Towards Efficient and Explainable Hate Speech Detection via Model Distillation
https://github.com/punyajoy/HateMonitors-HASOC
공식 코드HateMonitors: Language Agnostic Abuse Detection in Social Media
https://github.com/punyajoy/rgfs_ecai
공식 코드Rationale-Guided Few-Shot Classification to Detect Abusive Language
https://github.com/pxuab/emo2vec_wassa_paper
공식 코드Emo2Vec: Learning Generalized Emotion Representation by Multi-task Training
https://github.com/readerbench/semeval-2022-task-5
공식 코드https://github.com/tommasoc80/HateBERT
공식 코드HateBERT: Retraining BERT for Abusive Language Detection in English
https://github.com/urdufake/urdutask2021
공식 코드Overview of Abusive and Threatening Language Detection in Urdu at FIRE 2021
https://github.com/usydnlp/MACAS
공식 코드Detect All Abuse! Toward Universal Abusive Language Detection Models
https://github.com/younggns/comparative-abusive-lang
공식 코드Comparative Studies of Detecting Abusive Language on Twitter
https://github.com/JackonYang/maya
Comparative Studies of Detecting Abusive Language on Twitter
https://github.com/LucilleN/dv-classifier
Racial Bias in Hate Speech and Abusive Language Detection Datasets
https://github.com/UW-MSDS-DATA-598-Reproducibility-WI20/goel-modi-moroney-ramprasad-replication-project
Comparative Studies of Detecting Abusive Language on Twitter
https://github.com/abolim/Reproducibility-Research-Replication
Comparative Studies of Detecting Abusive Language on Twitter
https://github.com/asking28/offenseval2020
Racial Bias in Hate Speech and Abusive Language Detection Datasets
https://github.com/asking28/sentimix2020
Racial Bias in Hate Speech and Abusive Language Detection Datasets
https://github.com/t-davidson/hate-speech-and-offensive-language
Understanding Abuse: A Typology of Abusive Language Detection Subtasks
https://github.com/unitaryai/detoxify
Racial Bias in Hate Speech and Abusive Language Detection Datasets
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.