[2603.15636] AIDABench: AI Data Analytics Benchmark

Computer Science > Artificial Intelligence arXiv:2603.15636 (cs) [Submitted on 27 Feb 2026 (v1), last revised 27 Mar 2026 (this version, v2)] Title:AIDABench: AI Data Analytics Benchmark Authors:Yibo Yang, Fei Lei, Yixuan Sun, Yantao Zeng, Chengguang Lv, Jiancao Hong, Jiaojiao Tian, Tianyu Qiu, Xin Wang, Yanbing Chen, Yanjie Li, Zheng Pan, Xiaochen Zhou, Guanzhou Chen, Haoran Lv, Yuning Xu, Yue Ou, Haodong Liu, Shiqi He, Anya Jia, Yulei Xin, Huan Wu, Liang Liu, Jiaye Ge, Jianxin Dong, Dahua Lin, Wenxiu Sun View a PDF of the paper titled AIDABench: AI Data Analytics Benchmark, by Yibo Yang and 26 other authors View PDF HTML (experimental) Abstract:As AI-driven document understanding and processing tools become increasingly prevalent in real-world applications, the need for rigorous evaluation standards has grown increasingly urgent. Existing benchmarks and evaluations often focus on isolated capabilities or simplified scenarios, failing to capture the end-to-end task effectiveness required in practical settings. To address this gap, we introduce AIDABench, a comprehensive benchmark for evaluating AI systems on complex data analytics tasks in an end-to-end manner. AIDABench encompasses 600+ diverse document analysis tasks across three core capability dimensions: question answering, data visualization, and file generation. These tasks are grounded in realistic scenarios involving heterogeneous data types, including spreadsheets, databases, financial reports, and operational r...