Pytorch implementation of 'Explaining text classifiers with counterfactual representations'
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Updated
Apr 30, 2024 - Python
Pytorch implementation of 'Explaining text classifiers with counterfactual representations'
Replicate, update implementation of sent-bias: Social Bias in Sentence Encoders
A challenge set comparing male/female diacritization in Hebrew
🛒 Webscraper used to detect bias in Amazon product reviews for a product. Bias is determined through an original and rigorous algorithm, with the goal of producing a new, corrected, product star review from 1 to 5 based only on reviews that are considered to be 'unbiased'.
This git repository documents the code base used in a custom argument retrieval system. This git repository documents the code base used in a custom argument retrieval system. The system was build as a part of the Information Retrieval module at the University of Leipzig.
Code for the paper The Other Side of Compression: Measuring Bias in Pruned Transformers (IDA23)
Reddit Comment Moderator to Remove Ad Hominin, Very Biased (absolutes), and Negative Comments from Subreddits.
Addressing Political Bias in News Articles with Multinomial Regression
The project for my Master's Thesis on Algorithmic Discrimination in Natural Language Processing.
Image extraction and bias analysis
A bias bounty competition for income prediction. Using the pointer decision list method to improve group accuracy.
A reusable codebase for fast data science and machine learning experimentation, integrating various open-source tools to support automatic EDA, ML models experimentation and tracking, model inference, model explainability, bias, and data drift analysis.
Bias Analyzer for LLM prompts and responses
Analyzing identity biases with(in) machine learning and artificially intelligent systems. Sponsored by MunichRE.
Created for HackGT 2020. Sentiment Analysis model using supervised machine learning to detect bias in news articles. Won 3rd place for the NewsQ challenge.
An application of the WhizML codebase for an analysis of cardiovascular disease risk.
We study the general trend in bias reduction as newer pre-trained models are released. Three recent models ( ELECTRA, DeBERTa and DistilBERT) are chosen and evaluated against two bias benchmarks, StereoSet and CrowS-Pairs. They are compared to the baseline of BERT using the associated metrics
Face Mask Detection Application using AI, Keras, TensorFlow and OpenCV. It was created in the beginning of 2021 to help companies to validate the right use of face mask helping to prevent and reduce infection by covid-19 virus.
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