Search Results for author:
Found 5 papers, 1 papers with code
Guiding Enumerative Program Synthesis with Large Language Models
In this paper, we evaluate the abilities of LLMs to solve formal synthesis benchmarks by carefully crafting a library of prompts for the domain.
Reinforcement Learning and Data-Generation for Syntax-Guided Synthesis
To address this, we present a method for automatically generating training data for SyGuS based on anti-unification of existing first-order satisfiability problems, which we use to train our MCTS policy.
Neural Termination Analysis
We introduce a novel approach to the automated termination analysis of computer programs: we use neural networks to represent ranking functions.
A Study of Continuous Vector Representationsfor Theorem Proving
Applying machine learning to mathematical terms and formulas requires a suitable representation of formulas that is adequate for AI methods.
Goal-Oriented Conjecturing for Isabelle/HOL
We present PGT, a Proof Goal Transformer for Isabelle/HOL.
Logic in Computer Science
