hallucinations

#大语言模型#Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents

#自然语言处理#List of papers on hallucination detection in LLMs.

#大语言模型#✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models

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

#计算机科学#A curated list of trustworthy deep learning papers. Daily updating...

AI Testing Toolkit for AI applications

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

#自然语言处理#Attack to induce LLMs within hallucinations

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

#大语言模型#Hallucinations (Confabulations) Document-Based Benchmark for RAG. Includes human-verified questions and answers.

Dataset and evaluation script for "Evaluating Hallucinations in Chinese Large Language Models"

Code for the EMNLP 2024 paper "Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps"

#大语言模型#Initiative to evaluate and rank the most popular LLMs across common task types based on their propensity to hallucinate.

#自然语言处理#Framework for testing vulnerabilities of large language models (LLM).

mPLUG-HalOwl: Multimodal Hallucination Evaluation and Mitigating

[ICML 2024] Official implementation for "HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding"

#自然语言处理#An Easy-to-use Hallucination Detection Framework for LLMs.

Repository for the paper "Cognitive Mirage: A Review of Hallucinations in Large Language Models"

#大语言模型#Official repo for SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency

#大语言模型#The implementation for EMNLP 2023 paper ”Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators“