SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
01.AI · Beijing University of Posts and Telecommunications · Tongji University · Sichuan Agricultural University · Guangdong OPPO Mobile Telecommunications Corp.,Ltd. · 2077AI · University of the Chinese Academy of Sciences · Purdue University · Harbin Engineering University · Tsinghua University · Hokkaido University · Zhejiang University · zhejiang university · Peking University · Cornell University · The University of Manchester · Chinese University of Hong Kong(shenzhen) · University of Waterloo · Beijing University of Aeronautics and Astronautics · henzhen Institute of Advanced Technology, Chinese Academy of Sciences · ByteDance Inc. · Nanjing University of Science and Technology · China University of Geoscience Beijing · Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Chinese Academy of Sciences · Alibaba Group · Huawei Technologies Ltd. · Fudan University · University of Melbourne · national university of singaore, National University of Singapore · Hangzhou Dianzi University · University of Science and Technology of China · Centre for Digital Music, Queen Mary University of London · The Hong Kong University of Science and Technology (Guangzhou) · University of Manchester · Harvard University · stepfun · abaka · Facebook · Carnegie Mellon University · Department of Computer Science, Princeton University · Suzhou University · University of Science and Technology Beijing · Nanjing University · TikTok (Singapore) · Alibaba · Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences · Institute of automation, Chinese academy of science · Bytedance · Alibaba Qwen Pilot · Institute of Computing Science, Chinese Academy of Sciences · Mohamed bin Zayed University of Artificial Intelligence · Meta · Chinese Academy of Sciences, China · Abaka AI · Key Laboratory of Machine Perception · University of Michigan - Ann Arbor
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摘要
Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledge encompasses over 200 specialized disciplines, far exceeding the scope of existing benchmarks. The capabilities of LLMs in many of these specialized fields-particularly in light industry, agriculture, and service-oriented disciplines-remain inadequately evaluated. To address this gap, we present SuperGPQA, a comprehensive benchmark that evaluates graduate-level knowledge and reasoning capabilities across 285 disciplines. Our benchmark employs a novel Human-LLM collaborative filtering mechanism to eliminate trivial or ambiguous questions through iterative refinement based on both LLM responses and expert feedback. Our experimental results reveal significant room for improvement in the performance of current state-of-the-art LLMs across diverse knowledge domains (e.g., the reasoning-focused model Gemini-2.5-Pro achieved the highest accuracy of 63.56% on SuperGPQA), highlighting the considerable gap between current model capabilities and artificial general intelligence. Additionally, we present comprehensive insights from our management of a large-scale annotation process, involving over 80 expert annotators and an interactive Human-LLM collaborative system, offering valuable methodological guidance for future research initiatives of comparable scope.