5 papers
DiffLTM: Continuous Diffusions Large Tabular Models for Conditional Generation
Alankrita Bhatt, Mukur Gupta, Andrea Montanari +1
Conditional generation is a key capability to be supported by Large Tabular Models, enabling a number of applications. Accurate conditional generation has to contend with two key c…
Generating from Discrete Distributions Using Diffusions: Insights from Random Constraint Satisfaction Problems
Alankrita Bhatt, Mukur Gupta, Germain Kolossov +1
Generating data from discrete distributions is important for a number of application domains including text, tabular data, and genomic data. Several groups have recently used rando…
Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding
Adam Štorek, Mukur Gupta, Samira Hajizadeh +2
Large language models (LLMs) are increasingly deployed for understanding large codebases, but whether they understand operational semantics of long code context or rely on pattern…
XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants
Adam Štorek, Mukur Gupta, Noopur Bhatt +4
AI coding assistants are widely used for tasks like code generation. These tools now require large and complex contexts, automatically sourced from various origins$\unicode{x2014}$…
CodeSCM: Causal Analysis for Multi-Modal Code Generation
Mukur Gupta, Noopur Bhatt, Suman Jana
In this paper, we propose CodeSCM, a Structural Causal Model (SCM) for analyzing multi-modal code generation using large language models (LLMs). By applying interventions to CodeSC…