Loki: Open-source solution designed to automate the process of verifying factuality
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Updated
Jun 2, 2024 - Python
Loki: Open-source solution designed to automate the process of verifying factuality
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models. The first work to correct hallucinations in MLLMs.
RefChecker provides automatic checking pipeline and benchmark dataset for detecting fine-grained hallucinations generated by Large Language Models.
[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
[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
[ACL 2024] User-friendly evaluation framework: Eval Suite & Benchmarks: UHGEval, HaluEval, HalluQA, etc.
A comprehensive survey on Internal Consistency and Self-Feedback in Large Language Models.
😎 up-to-date & 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"
[IJCAI 2024] FactCHD: Benchmarking Fact-Conflicting Hallucination Detection
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
Code & Data for our Paper "Alleviating Hallucinations of Large Language Models through Induced Hallucinations"
[NeurIPS 2024] Knowledge Circuits in Pretrained Transformers
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.
OLAPH: Improving Factuality in Biomedical Long-form Question Answering
"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
Visual Correspondence Hallucination: Towards Geometric Reasoning (Under Review)
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