Recent years have seen impressive performance of transformer-based models on different
natural language processing tasks. However, it is not clear to what degree the transformers …

Abstract Machine learning (ML) systems in natural language processing (NLP) face
significant challenges in generalizing to out-of-distribution (OOD) data, where the test …

Complex reasoning aims to draw a correct inference based on complex rules. As a hallmark
of human intelligence, it involves a degree of explicit reading comprehension, interpretation …

Large language models have shown impressive results for multi-hop mathematical
reasoning when the input question is only textual. Many mathematical reasoning problems …

We present LogiGAN, an unsupervised adversarial pre-training framework for improving
logical reasoning abilities of language models. Upon automatic identification of logical …

This survey summarises the most recent methods for building and assessing helpful, honest,
and harmless neural language models, considering small, medium, and large-size models …

This study investigates self-assessment tendencies in Large Language Models (LLMs),
examining if patterns resemble human cognitive biases like the Dunning–Kruger effect …