15 citations · 19 across the 9 of their papers we have counts for
9 papers
Semantically Aligned Question and Code Generation for Automated Insight Generation
Ananya Singha, Bhavya Chopra, Anirudh Khatry +6
Automated insight generation is a common tactic for helping knowledge workers, such as data scientists, to quickly understand the potential value of new and unfamiliar data. Unfort…
CodeFusion: A Pre-trained Diffusion Model for Code Generation
Mukul Singh, José Cambronero, Sumit Gulwani +3
Imagine a developer who can only change their last line of code, how often would they have to start writing a function from scratch before it is correct? Auto-regressive models for…
FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language
Mukul Singh, José Cambronero, Sumit Gulwani +5
Formatting is an important property in tables for visualization, presentation, and analysis. Spreadsheet software allows users to automatically format their tables by writing data-…
TST: Target Similarity Tuning Meets the Real World
Anirudh Khatry, Sumit Gulwani, Priyanshu Gupta +4
Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance. I…
DataVinci: Learning Syntactic and Semantic String Repairs
Mukul Singh, José Cambronero, Sumit Gulwani +3
String data is common in real-world datasets: 67.6% of values in a sample of 1.8 million real Excel spreadsheets from the web were represented as text. Systems that successfully cl…
Demonstration of CORNET: A System For Learning Spreadsheet Formatting Rules By Example
Mukul Singh, Jose Cambronero, Sumit Gulwani +3
Data management and analysis tasks are often carried out using spreadsheet software. A popular feature in most spreadsheet platforms is the ability to define data-dependent formatt…