48 citations · 76 across the 17 of their papers we have counts for
5 papers · 1 filter
Microsaccade-Inspired Probing: Positional Encoding Perturbations Reveal LLM Misbehaviours
Rui Melo, Rui Abreu, Corina S. Pasareanu
We draw inspiration from microsaccades, tiny involuntary eye movements that reveal hidden dynamics of human perception, to propose an analogous probing method for large language mo…
Worst-Case Symbolic Constraints Analysis and Generalisation with Large Language Models
Daniel Koh, Yannic Noller, Corina S. Pasareanu +2
Large language models (LLMs) have demonstrated strong performance on coding tasks such as generation, completion and repair, but their ability to handle complex symbolic reasoning…
Relational Hoare Logic for Realistically Modelled Machine Code
Denis Mazzucato, Abdalrhman Mohamed, Juneyoung Lee +4
Many security- and performance-critical domains, such as cryptography, rely on low-level verification to minimize the trusted computing surface and allow code to be written directl…
Enhancing LLM Code Generation with Ensembles: A Similarity-Based Selection Approach
Tarek Mahmud, Bin Duan, Corina Pasareanu +1
Ensemble learning has been widely used in machine learning to improve model robustness, accuracy, and generalization, but has not yet been applied to code generation tasks with lar…
Agentic AI Software Engineers: Programming with Trust
Abhik Roychoudhury, Corina Pasareanu, Michael Pradel +1
Large Language Models (LLMs) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (A…