EdinburghNLP / awesome-hallucination-detectionLinks
List of papers on hallucination detection in LLMs.
☆997Updated 3 weeks ago
Alternatives and similar repositories for awesome-hallucination-detection
Users that are interested in awesome-hallucination-detection are comparing it to the libraries listed below
Sorting:
- SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models☆583Updated last year
- This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.☆532Updated last year
- Codebase for reproducing the experiments of the semantic uncertainty paper (short-phrase and sentence-length experiments).☆390Updated last year
- Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models☆791Updated 6 months ago
- ☆625Updated 4 months ago
- Must-read Papers on Knowledge Editing for Large Language Models.☆1,203Updated 4 months ago
- Representation Engineering: A Top-Down Approach to AI Transparency☆918Updated last year
- The papers are organized according to our survey: Evaluating Large Language Models: A Comprehensive Survey.☆787Updated last year
- ☆477Updated 4 months ago
- [ICML 2024] TrustLLM: Trustworthiness in Large Language Models☆614Updated 5 months ago
- A package to evaluate factuality of long-form generation. Original implementation of our EMNLP 2023 paper "FActScore: Fine-grained Atomic…☆408Updated 7 months ago
- A reading list on LLM based Synthetic Data Generation 🔥☆1,484Updated 6 months ago
- Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large Language Models☆388Updated last year
- This repository collects all relevant resources about interpretability in LLMs☆385Updated last year
- Evaluate your LLM's response with Prometheus and GPT4 💯☆1,017Updated 7 months ago
- Generative Representational Instruction Tuning☆679Updated 5 months ago
- A curated list of Large Language Model (LLM) Interpretability resources.☆1,453Updated 5 months ago
- This is a collection of research papers for Self-Correcting Large Language Models with Automated Feedback.☆558Updated last year
- Github repository for "RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models"☆215Updated last year
- Stanford NLP Python library for understanding and improving PyTorch models via interventions☆834Updated last month
- Official implementation for the paper "DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models"☆524Updated 10 months ago
- Inference-Time Intervention: Eliciting Truthful Answers from a Language Model☆560Updated 10 months ago
- LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.☆758Updated last year
- Aligning Large Language Models with Human: A Survey☆739Updated 2 years ago
- LLM hallucination paper list☆327Updated last year
- A curated list of LLM Interpretability related material - Tutorial, Library, Survey, Paper, Blog, etc..☆286Updated 8 months ago
- A collection of benchmarks and datasets for evaluating LLM.☆530Updated last year
- Code for paper "G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment"☆397Updated last year
- ☆393Updated last week
- Reading list of hallucination in LLMs. Check out our new survey paper: "Siren’s Song in the AI Ocean: A Survey on Hallucination in Large …☆1,066Updated 2 months ago