More than one hundred benchmarks have been developed to test the commonsense
knowledge and commonsense reasoning abilities of artificial intelligence (AI) systems …

Pretraining a language model (LM) on text has been shown to help various downstream
NLP tasks. Recent works show that a knowledge graph (KG) can complement text data …

Role-play has long been used as an active learning technique in educational and training
contexts. In particular, Edu-larp (a structured, live action roleplay experience that teaches …

Large language models (LLMs) have shown remarkable generalization capability with
exceptional performance in various language modeling tasks. However, they still exhibit …

Knowledge underpins reasoning. Recent research demonstrates that when relevant
knowledge is provided as additional context to commonsense question answering (QA), it …

Recent advances in pre-trained language models (PLMs) have facilitated the development
ofcommonsense reasoning tasks. However, existing methods rely on multi-hop …

While commonsense knowledge acquisition and reasoning has traditionally been a core
research topic in the knowledge representation and reasoning community, recent years …

Most of today's AI systems focus on using self-attention mechanisms and transformer
architectures on large amounts of diverse data to achieve impressive performance gains. In …

Knowledge in NLP has been a rising trend especially after the advent of large-scale pre-
trained models. Knowledge is critical to equip statistics-based models with common sense …

Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in
addressing the challenges of Large Language Models (LLMs) without necessitating …