Papers with data science tasks
AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science (2025.findings-emnlp)
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| Challenge: | Large language models are increasingly used to automate data analysis, but data science tasks often admit multiple statistically valid solutions. |
| Approach: | They propose a framework to evaluate LLM-generated code and assess its reproducibility . they introduce two reproducibility-enhancing prompting strategies and benchmark them against standard prompting . |
| Outcome: | The proposed framework improves reproducibility of large language models . it provides a foundation for transparent, reliable, and efficient human–AI collaboration in data science. |
The Lexometer: A Shiny Application for Exploratory Analysis and Visualization of Corpus Data (2022.lrec-1)
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| Challenge: | Lexometer is a data science application that integrates data analysis and visualization functions into an easy-to-use graphical user interface. |
| Approach: | They propose a Shiny application that integrates data analysis and visualization functions into an easy-to-use graphical user interface. |
| Outcome: | The Lexometer integrates numerous data analysis and visualization functions into an easy-to-use graphical user interface. |
SpreadNaLa: A Naturalistic Code Generation Evaluation Dataset of Spreadsheet Formulas (2024.lrec-main)
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| Challenge: | Existing datasets primarily target the use of code generation models to aid expert programmers in writing code. |
| Approach: | They propose a natural language code generation model that can translate English descriptions to spreadsheet formulas that can be used to do everyday data processing tasks. |
| Outcome: | The proposed model performs best among the evaluated methods but generates formulas that differ from human-generated ones. |