Lookback-Lens

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents

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

List of papers on hallucination detection in LLMs.

??Woodpecker: Hallucination Correction for Multimodal Large Language Models

Benchmarking long-form factuality in large language models. Original code for our paper "Long-form factuality in large language models".

Official implementation for the paper "DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models"

LettuceDetect is a hallucination detection framework for RAG applications.

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

A package to evaluate factuality of long-form generation. Original implementation of our EMNLP 2023 paper "FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation"