IINemo/lm-polygraph

[JMLR 2026] UQLM: A Python package for LLM hallucination detection using uncertainty quantification

Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparent evaluation of foundation models, including large language models (LLMs) and multimodal models.

List of papers on hallucination detection in LLMs.

LiveBench: A Challenging, Contamination-Free LLM Benchmark

Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

[EMNLP 2024 Demo] MarkLLM: An Open-Source Toolkit for LLM Watermarking

This repository provides a benchmark for prompt injection attacks and defenses in LLMs

A unified evaluation framework for large language models

The LLM Evaluation Framework