BABE: Biology Arena BEnchmark

• URL: http://arxiv.org/abs/2602.05857v1
• Date: Thu, 05 Feb 2026 16:39:20 GMT
• Title: BABE: Biology Arena BEnchmark
• Authors: Junting Zhou, Jin Chen, Linfeng Hao, Denghui Cao, Zheyu Wang, Qiguang Chen, Chaoyou Fu, Jiaze Chen, Yuchen Wu, Ge Zhang, Mingxuan Wang, Wenhao Huang, Tong Yang,
• Abstract summary: BABE is a benchmark designed to evaluate the experimental reasoning capabilities of biological AI systems.<n>Our benchmark provides a robust framework for assessing how well AI systems can reason like practicing scientists.
• Score: 51.53220868983288
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid evolution of large language models (LLMs) has expanded their capabilities from basic dialogue to advanced scientific reasoning. However, existing benchmarks in biology often fail to assess a critical skill required of researchers: the ability to integrate experimental results with contextual knowledge to derive meaningful conclusions. To address this gap, we introduce BABE(Biology Arena BEnchmark), a comprehensive benchmark designed to evaluate the experimental reasoning capabilities of biological AI systems. BABE is uniquely constructed from peer-reviewed research papers and real-world biological studies, ensuring that tasks reflect the complexity and interdisciplinary nature of actual scientific inquiry. BABE challenges models to perform causal reasoning and cross-scale inference. Our benchmark provides a robust framework for assessing how well AI systems can reason like practicing scientists, offering a more authentic measure of their potential to contribute to biological research.

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