MLGroupJLU/LLM-eval-survey🔥 active
The official GitHub page for the survey paper "A Survey on Evaluation of Large Language Models".
[ACM MM 2026] Code for paper "Omni-SafetyBench: A Benchmark for Safety Evaluation of Audio-Visual Large Language Models".
$ git clone https://github.com/THU-BPM/Omni-SafetyBench.gitThe official GitHub page for the survey paper "A Survey on Evaluation of Large Language Models".
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[EMNLP 2024 Demo] MarkLLM: An Open-Source Toolkit for LLM Watermarking
[EMNLP 2024 & AAAI 2026] A powerful toolkit for compressing large models including LLMs, VLMs, and video generative models.
[ICML 2024] TrustLLM: LLM trustworthiness evaluation across truthfulness, safety, fairness, robustness, privacy and ethics. Python/CLI toolkit for local models, compatible APIs and AI agent orchestration.
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Dataset and benchmark for RAG on company internal documents.
Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new information becomes available, mirroring real-world challenges.
Data from GitHub · snapshot Nov 13, 2026