Interest in logics with some notion of real-valued truths has existed since at least Boole and
has been increasing in AI due to the emergence of neuro-symbolic approaches, though …

Neuro-symbolic learning (NSL) models complex symbolic rule patterns into latent variable
distributions by neural networks, which reduces rule search space and generates unseen …

Many-valued logics in general, and fuzzy logics in particular, usually focus on a notion of
consequence based on preservation of full truth, typical represented by the value 1 in the …

As a well-known optimization framework, the Alternating Direction Method of Multipliers
(ADMM) has achieved tremendous success in many classification and regression …

The rapid advancement of Large Language Models (LLMs) has transformed various
scientific domains, yet their effective application in specialized fields such as geoscience …

In this paper, we study how to represent a directed graph as a SAT problem. We study those
directed graphs which consists of two strongly connected components (SCC). We reuse the …

Statutory reasoning is the task of determining how laws apply to a legal case. This is a basic
skill for lawyers, and in its computational form, a fundamental task for legal Artificial …

• Real world data contains logical inconsistencies due to which the original LNN does not
perform well.• Humans have been familiar with convex optimization for many years …