3 papers
cs.SE2025
Quality Assessment of Tabular Data using Large Language Models and Code Generation
Ashlesha Akella, Akshar Kaul, Krishnasuri Narayanam +1
Reliable data quality is crucial for downstream analysis of tabular datasets, yet rule-based validation often struggles with inefficiency, human intervention, and high computationa…
cs.LG2025
Data Wrangling Task Automation Using Code-Generating Language Models
Ashlesha Akella, Krishnasuri Narayanam
Ensuring data quality in large tabular datasets is a critical challenge, typically addressed through data wrangling tasks. Traditional statistical methods, though efficient, cannot…
cs.AI2024
QUIS: Question-guided Insights Generation for Automated Exploratory Data Analysis
Abhijit Manatkar, Ashlesha Akella, Parthivi Gupta +1
Discovering meaningful insights from a large dataset, known as Exploratory Data Analysis (EDA), is a challenging task that requires thorough exploration and analysis of the data. A…