NeurASP: Embracing Neural Networks into Answer Set Programming

1 code implementation • 15 Jul 2023 • Zhun Yang, Adam Ishay, Joohyung Lee

We present NeurASP, a simple extension of answer set programs by embracing neural networks.

Leveraging Large Language Models to Generate Answer Set Programs

1 code implementation • 15 Jul 2023 • Adam Ishay, Zhun Yang, Joohyung Lee

Specifically, we employ an LLM to transform natural language descriptions of logic puzzles into answer set programs.

Formal Logic In-Context Learning

Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text

1 code implementation • 15 Jul 2023 • Zhun Yang, Adam Ishay, Joohyung Lee

It only needs a few examples to guide the LLM's adaptation to a specific task, along with reusable ASP knowledge modules that can be applied to multiple tasks.

Language Modelling Large Language Model +1

Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer

1 code implementation • 10 Jul 2023 • Zhun Yang, Adam Ishay, Joohyung Lee

Constraint satisfaction problems (CSPs) are about finding values of variables that satisfy the given constraints.