Popular GitHub Repositories for Mitigation

A Python package to assess and improve fairness of machine learning models.

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

Tensor network based quantum software framework for the NISQ era

WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!

up-to-date curated list of state-of-the-art Large vision language models hallucinations research work, papers & resources

This is an open-source tool to assess and improve the trustworthiness of AI systems.

Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.

[ACL 2024] ANAH & [NeurIPS 2024] ANAH-v2 & [ICLR 2025] Mask-DPO

Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).

The code repository for the CURLoRA research paper. Stable LLM continual fine-tuning and catastrophic forgetting mitigation.

Oracle Guardian AI Open Source Project is a library consisting of tools to assess fairness/bias and privacy of machine learning models and data sets.

A novel alignment framework that leverages image retrieval to mitigate hallucinations in Vision Language Models.

Discover and Cure: Concept-aware Mitigation of Spurious Correlation (ICML 2023)

Machine Learning Based - Intrusion Detection System

Implementation code for the paper "Learning Resilient Radio Resource Management Policies with Graph Neural Networks" (IEEE Transactions on Signal Processing)

Official code of "Discover and Mitigate Unknown Biases with Debiasing Alternate Networks" (ECCV 2022)

Demographic Bias of Vision-Language Foundation Models in Medical Imaging

Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions

Implementation of iMolCLR: "Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast" in PyG.