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EMNLP 2024mainmain

DataTales: A Benchmark for Real-World Intelligent Data Narration

Yajing Yang, Qian Liu, Min-Yen Kan

national university of singaore, National University of Singapore · Sea AI Lab · National University of Singapore

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2024.emnlp-main.601 ↗

摘要

We introduce DataTales, a novel benchmark designed to assess the proficiency of language models in data narration, a task crucial for transforming complex tabular data into accessible narratives. Existing benchmarks often fall short in capturing the requisite analytical complexity for practical applications. DataTales addresses this gap by offering 4.9k financial reports paired with corresponding market data, showcasing the demand for models to create clear narratives and analyze large datasets while understanding specialized terminology in the field. Our findings highlights the significant challenge that language models face in achieving the necessary precision and analytical depth for proficient data narration, suggesting promising avenues for future model development and evaluation methodologies.