16 citations · 22 across the 5 of their papers we have counts for
5 papers
Guiding Enumerative Program Synthesis with Large Language Models
Yixuan Li, Julian Parsert, Elizabeth Polgreen
Pre-trained Large Language Models (LLMs) are beginning to dominate the discourse around automatic code generation with natural language specifications. In contrast, the best-perfor…
Reinforcement Learning and Data-Generation for Syntax-Guided Synthesis
Julian Parsert, Elizabeth Polgreen
Program synthesis is the task of automatically generating code based on a specification. In Syntax-Guided Synthesis (SyGuS) this specification is a combination of a syntactic templ…
Neural Termination Analysis
Mirco Giacobbe, Daniel Kroening, Julian Parsert
We introduce a novel approach to the automated termination analysis of computer programs: we use neural networks to represent ranking functions. Ranking functions map program state…
A Study of Continuous Vector Representationsfor Theorem Proving
Stanisław Purgał, Julian Parsert, Cezary Kaliszyk
Applying machine learning to mathematical terms and formulas requires a suitable representation of formulas that is adequate for AI methods. In this paper, we develop an encoding t…
Goal-Oriented Conjecturing for Isabelle/HOL
Yutaka Nagashima, Julian Parsert
We present PGT, a Proof Goal Transformer for Isabelle/HOL. Given a proof goal and its background context, PGT attempts to generate conjectures from the original goal by transformin…