DataTales: A Benchmark for Real-World Intelligent Data Narration
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 22 of its 50 references that are in the map. First posted on arXiv 23 Oct 2024.
Builds on
22 of 50 references.
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10 more
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Built on by
Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025T2R-bench: A Benchmark for Generating Article-Level Reports from Real World Industrial Tablescited by 5
- 2025KAHAN: Knowledge-Augmented Hierarchical Analysis and Narration for Financial Data Narrationcited by 1
- 2026AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generationcited by 0
- 2026AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generation1 Sep 2026
- 2025KAHAN: Knowledge-Augmented Hierarchical Analysis and Narration for Financial Data Narration21 Sep 2025
- 2025T2R-bench: A Benchmark for Generating Article-Level Reports from Real World Industrial Tables27 Aug 2025