Popular GitHub Repositories for Hallucination

Loki: Open-source solution designed to automate the process of verifying factuality

??Woodpecker: Hallucination Correction for Multimodal Large Language Models

RefChecker provides automatic checking pipeline and benchmark dataset for detecting fine-grained hallucinations generated by Large Language Models.

[CVPR'24] HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models

[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

? curated list of awesome LMM hallucinations papers, methods & resources.

Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"

[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers

[IJCAI 2024] FactCHD: Benchmarking Fact-Conflicting Hallucination Detection

Code & Data for our Paper "Alleviating Hallucinations of Large Language Models through Induced Hallucinations"

Official repo for the paper PHUDGE: Phi-3 as Scalable Judge. Evaluate your LLMs with or without custom rubric, reference answer, absolute, relative and much more. It contains a list of all the available tool, methods, repo, code etc to detect hallucination, LLM evaluation, grading and much more.

"Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases" by Jiarui Li and Ye Yuan and Zehua Zhang

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

Materials for the course Principles of AI: LLMs at UPenn (Stat 9911, Spring 2025). LLM architectures, training paradigms (pre- and post-training, alignment), test-time computation, reasoning, safety and robustness (jailbreaking, oversight, uncertainty), representations, interpretability (circuits), etc.

Visual Correspondence Hallucination: Towards Geometric Reasoning (Under Review)

Code scanner to check for issues in prompts and LLM calls

NoMIRACL: A multilingual hallucination evaluation dataset to evaluate LLM robustness in RAG against first-stage retrieval errors on 18 languages.

??Code and benchmark for our Findings of ACL 2024 paper - "TimeChara: Evaluating Point-in-Time Character Hallucination of Role-Playing Large Language Models"

Poison as Cure: Visual Noise for Mitigating Object Hallucinations in LVMs

Can Knowledge Editing Really Correct Hallucinations? (ICLR 2025)