hallucination

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

#Awesome#Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

#大语言模型#UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

#大语言模型#✨✨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.

#大语言模型#[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

#大语言模型#[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Explore concepts like Self-Correct, Self-Refine, Self-Improve, Self-Contradict, Self-Play, and Self-Knowledge, alongside o1-like reasoning elevation🍓 and hallucination alleviation🍄.

#大语言模型#[ACL 2024] User-friendly evaluation framework: Eval Suite & Benchmarks: UHGEval, HaluEval, HalluQA, etc.

#大语言模型#[ICLR 2025] LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation

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

#大语言模型#Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"

#自然语言处理#[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers

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

#自然语言处理#[IJCAI 2024] FactCHD: Benchmarking Fact-Conflicting Hallucination Detection

#自然语言处理#[ICLR 2025] MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation

This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.

#大语言模型#Code scanner to check for issues in prompts and LLM calls

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