TruthfulQA

Truth detector

Evaluating model performance on human falsehoods in language models

TruthfulQA: Measuring How Models Imitate Human Falsehoods

GitHub

631 stars
8 watching
74 forks
Language: Jupyter Notebook
last commit: almost 3 years ago

Related projects:

RepositoryDescriptionStars
rowanz/groverA framework for defending against neural fake news through both generation and detection of fake news articles.918
findalexli/scigraphqaA dataset and benchmarking framework for evaluating the performance of large language models on multi-turn question answering tasks for scientific graphs.38
nyu-mll/bbqA dataset and benchmarking framework to evaluate the performance of question answering models on detecting and mitigating social biases.92
gair-nlp/factoolAn open-source framework for detecting factual errors in AI-generated text839
0x4d31/deception-as-detectionMaps deception detection techniques to the ATT&CK framework and provides documentation for security professionals287
adoreste/truehunterDetects encrypted files using a fast and memory efficient approach without external dependencies.30
jiasenlu/hiecoattenvqaA framework for training Hierarchical Co-Attention models for Visual Question Answering using preprocessed data and a specific image model.349
strongqa/howitzerA Ruby-based framework for acceptance testing with flexibility and scalability for different testing tools and cloud services.261
yosefk/checkedthreadsA parallelism framework that detects and prevents race conditions in multithreaded code by automatically load balancing and using Valgrind-based instrumentation.290
truera/trulensA tool to evaluate and track the performance of large language model (LLM) experiments2,233
masaiahhan/correlationqaAn investigation into the relationship between misleading images and hallucinations in large language models8
rifkybujana/fndAn AI-powered tool that detects whether news articles are fake or not8
ai4risk/antifraudDevelops and evaluates machine learning models for detecting financial fraud195
jagilley/fact-checkerA tool for fact-checking LLM outputs with self-ask using prompt chaining289
yg-smile/rl_vvc_datasetA collection of benchmarks and implementations for testing reinforcement learning-based Volt-VAR control algorithms20