30 citations · 52 across the 15 of their papers we have counts for
17 papers
A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets
Tejas Agrawal, Vu Le, Sumit Gulwani +1
Predictive code completion greatly accelerates how quickly developers work. In spreadsheets, despite being much more common, such auto-completion features are virtually non-existen…
Tabularis Formatus: Predictive Formatting for Tables
Mukul Singh, José Cambronero, Sumit Gulwani +2
Spreadsheet manipulation software are widely used for data management and analysis of tabular data, yet the creation of conditional formatting (CF) rules remains a complex task req…
Diffusion is a code repair operator and generator
Mukul Singh, Gust Verbruggen, Vu Le +1
Code diffusion models generate code by iteratively removing noise from the latent representation of a code snippet. During later steps of the diffusion process, when the code snipp…
LLM-Guided Compositional Program Synthesis
Ruhma Khan, Sumit Gulwani, Vu Le +3
Program synthesis from input-output examples, also called programming by example (PBE), has had tremendous impact on automating end-user tasks. Large language models (LLMs) have th…
An Empirical Study of Validating Synthetic Data for Formula Generation
Usneek Singh, José Cambronero, Sumit Gulwani +5
Large language models (LLMs) can be leveraged to help with writing formulas in spreadsheets, but resources on these formulas are scarce, impacting both the base performance of pre-…
Assessing GPT4-V on Structured Reasoning Tasks
Mukul Singh, José Cambronero, Sumit Gulwani +2
Multi-modality promises to unlock further uses for large language models. Recently, the state-of-the-art language model GPT-4 was enhanced with vision capabilities. We carry out a…
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…
Personalized action suggestions in low-code automation platforms
Saksham Gupta, Gust Verbruggen, Mukul Singh +2
Automation platforms aim to automate repetitive tasks using workflows, which start with a trigger and then perform a series of actions. However, with many possible actions, the use…
FLAME: A small language model for spreadsheet formulas
Harshit Joshi, Abishai Ebenezer, José Cambronero +5
Spreadsheets are a vital tool for end-user data management. Using large language models for formula authoring assistance in these environments can be difficult, as these models are…
Repairing Bugs in Python Assignments Using Large Language Models
Jialu Zhang, José Cambronero, Sumit Gulwani +4
Students often make mistakes on their introductory programming assignments as part of their learning process. Unfortunately, providing custom repairs for these mistakes can require…
Repair Is Nearly Generation: Multilingual Program Repair with LLMs
Harshit Joshi, José Cambronero, Sumit Gulwani +3
Most programmers make mistakes when writing code. Some of these mistakes are small and require few edits to the original program -- a class of errors recently termed last mile mist…
CORNET: Learning Table Formatting Rules By Example
Mukul Singh, José Cambronero, Sumit Gulwani +4
Spreadsheets are widely used for table manipulation and presentation. Stylistic formatting of these tables is an important property for both presentation and analysis. As a result,…
Human-Machine Collaboration for Democratizing Data Science
Clément Gautrais, Yann Dauxais, Stefano Teso +3
Everybody wants to analyse their data, but only few posses the data science expertise to to this. Motivated by this observation we introduce a novel framework and system \textsc{Vi…