Meeseeks is an instruction-following benchmark designed to evaluate how well models can adhere to user instructions in a multi-turn scenario.A key feature of Meeseeks is its self-correction loop, where models receive structured feedback and must refine their responses accordingly.
This benchmark provides a realistic evaluation of a model’s adaptability, instruction adherence, and iterative improvement.
📊 Leaderboard… See the full description on the dataset page: https://huggingface.co/datasets/wang4146/Meeseeks-high-quality.
