BBQ
Bias detector
A dataset and benchmarking framework to evaluate the performance of question answering models on detecting and mitigating social biases.
Repository for the Bias Benchmark for QA dataset.
87 stars
8 watching
21 forks
Language: Python
last commit: 11 months ago Related projects:
Repository | Description | Stars |
---|---|---|
modeloriented/fairmodels | A tool for detecting bias in machine learning models and mitigating it using various techniques. | 86 |
algofairness/blackboxauditing | A software package for auditing and analyzing machine learning models to detect unfair biases | 130 |
privacytrustlab/bias_in_fl | Analyzing bias propagation in federated learning algorithms to improve group fairness and robustness | 11 |
dssg/aequitas | Toolkit to audit and mitigate biases in machine learning models | 694 |
i-gallegos/fair-llm-benchmark | Compiles bias evaluation datasets and provides access to original data sources for large language models | 110 |
13o-bbr-bbq/machine_learning_security | A collection of tools and techniques for applying machine learning to improve security in software applications | 1,979 |
ethicalml/xai | An eXplainability toolbox for machine learning that enables data analysis and model evaluation to mitigate biases and improve performance | 1,125 |
megantosh/fairness_measures_code | This repository contains implementations of measures to quantify discrimination in data | 38 |
iamgroot42/mimir | Measures memorization in Large Language Models (LLMs) to detect potential privacy issues | 121 |
freedomintelligence/mllm-bench | Evaluates and compares the performance of multimodal large language models on various tasks | 55 |
responsiblyai/responsibly | A toolkit for auditing and mitigating bias in machine learning systems | 94 |
seldonio/alibi-detect | A Python library for detecting outliers, adversarial examples, and data drift in various types of data | 2,247 |
visionjo/facerec-bias-bfw | This project provides a data proxy to evaluate bias in facial recognition systems across demographic groups. | 46 |
nyu-mll/glue-baselines | An implementation of multi-task learning approaches to learning sentence representations for the GLUE benchmark | 773 |
cisco-open/inclusive-language | Tools and resources for identifying biased language in code and content. | 21 |