Large Language Models (LLMs) have greatly propelled the progress in natural language
(NL)-centric tasks based on NL interface. However, the NL form is not enough for world …

This paper explores the integration of two AI subdisciplines employed in the development of
artificial agents that exhibit intelligent behavior: Large Language Models (LLMs) and …

We tackle the task of enriching ontologies by automatically translating natural language (NL)
into Description Logic (DL). Since Large Language Models (LLMs) are the best tools for …

The opioid crisis has been one of the most critical society concerns in the United States.
Although the medication assisted treatment (MAT) is recognized as the most effective …

Symbols (or more broadly, non-natural language textual representations) such as numerical
sequences, molecular formulas, and table delimiters widely exist, playing important roles in …

In this paper, we explore a new way for user targeting, where non-expert marketers could
select their target users solely given demands in natural language form. The key to this issue …

Large language models (LLMs) have shown significant achievements in solving a wide
range of tasks. Recently, LLMs' capability to store, retrieve and infer with symbolic …

Logical fallacies are common errors in reasoning that undermine the logic of an argument.
Automatically detecting logical fallacies has important applications in tracking …

Requirements engineering plays a pivotal role in the development of safety-critical systems.
However, the process is usually a manual one and can lead to errors and inconsistencies in …

Large Language Models (LLMs) have shown superior capability to solve reasoning
problems with programs. While being a promising direction, most of such frameworks are …