Abstract Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining
deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its …

Harnessing logical reasoning ability is a comprehensive natural language understanding
endeavor. With the release of Generative Pretrained Transformer 4 (GPT-4), highlighted as" …

A hallmark of abstract reasoning is the ability to systematically perform algebraic operations
over variables that can be bound to any entity (Newell, 1980; Fodor and Pylyshyn, 1988): the …

In the NLP community, recent years have seen a surge of research activities that address
machines' ability to perform deep language understanding which goes beyond what is …

This paper presents the task on the evaluation of Compositional Distributional Semantics
Models on full sentences organized for the first time within SemEval-2014. Participation was …

Abductive reasoning is inference to the most plausible explanation. For example, if Jenny
finds her house in a mess when she returns from work, and remembers that she left a …

Knowledge bases (KB), both automatically and manually constructed, are often incomplete---
many valid facts can be inferred from the KB by synthesizing existing information. A popular …

Structural analysis methods (eg, probing and feature attribution) are increasingly important
tools for neural network analysis. We propose a new structural analysis method grounded in …

Despite the seeming success of contemporary grounded text generation systems, they often
tend to generate factually inconsistent text with respect to their input. This phenomenon is …

NLP research on logical reasoning regains momentum with the recent releases of a handful
of datasets, notably LogiQA and Reclor. Logical reasoning is exploited in many probing …