Bachelor's thesis on removing hate from online comments using paraphrasing: algorithm DPhate
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Updated
Apr 8, 2022 - Python
Bachelor's thesis on removing hate from online comments using paraphrasing: algorithm DPhate
Data Challenge leading to "A Multidisciplinary Lens of Bias in Hate Speech" (ASONAM 2023)
This GitHub repository contains code and resources for a multilingual offensive speech detection model, designed to detect offensive speech in textual data for English and Hindi.
This is the official implementation of our paper Robust Hate Speech Detection via Mitigating Spurious Correlations (Tiwari et al., AACL-IJCNLP 2022)
Hate Speech Detector with Python
The Backend service for Testing harness. Testing harness is an integrated dashboard to evaluate the capabilities of various LLM models Resources
Improving Zero-Shot Cross-Lingual Hate Speech Detection with Pseudo-Label Fine-Tuning of Transformer Language Models
Training code and public data for the paper "A Legal Approach to Hate Speech - Operationalizing the EU's Legal Framework against the Expression of Hatred as an NLP Task"
In this project we have tried to do multi-label hate-speech classification in Bengali and Hindi language using fill-mask transformer models.
Detecting Hate Speech in Online Spaces using NLP
Code for the paper The Other Side of Compression: Measuring Bias in Pruned Transformers (IDA23)
This repository contains the dataset and implementation details of the paper: Unmasking the Hidden Meaning: Bridging Implicit and Explicit Hate Speech Embedding Representations accepted in the findings of EMNLP 2023.
Final project for the course LT2318 Artificial Intelligence: Cognitive Systems. The project concerns multimodal hate speech detection in memes.
CSC2612 Course Project
Classification of hate speech and implicitness of hate speech, using Transformer language models (BERT). This repository can be used as an introduction to text classification with BERT-like models.
a novel Romanian language dataset for offensive message detection with manually annotated comment from a local Romanian news website (stiri de cluj) into five classes
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