Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents

List of papers on hallucination detection in LLMs.

✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models. The first work to correct hallucinations in MLLMs.

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

A curated list of trustworthy deep learning papers. Daily updating...

Alignment toolkit to safeguards LLMs

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

Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"

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

Attack to induce LLMs within hallucinations

Initiative to evaluate and rank the most popular LLMs across common task types based on their propensity to hallucinate.

mPLUG-HalOwl: Multimodal Hallucination Evaluation and Mitigating

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

Hallucinations (Confabulations) Document-Based Benchmark for RAG

An Easy-to-use Hallucination Detection Framework for LLMs.

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

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

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

DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models

Code for Controlling Hallucinations at Word Level in Data-to-Text Generation (C. Rebuffel, M. Roberti, L. Soulier, G. Scoutheeten, R. Cancelliere, P. Gallinari)