This article surveys and organizes research works in a new paradigm in natural language
processing, which we dub “prompt-based learning.” Unlike traditional supervised learning …

The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …

Deploying large language models (LLMs) is challenging because they are memory
inefficient and compute-intensive for practical applications. In reaction, researchers train …

Large language models (LLMs) have demonstrated remarkable capabilities in language
generation, understanding, and few-shot learning in recent years. An extensive body of work …

Finetuning language models on a collection of datasets phrased as instructions has been
shown to improve model performance and generalization to unseen tasks. In this paper we …

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in
activities such as problem solving, decision making, and critical thinking. In recent years …

Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …

Large Language Models (LLMs) have shown promise in the autonomous driving sector,
particularly in generalization and interpretability. We introduce a unique objectlevel …

Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …

Pretrained large language models (LLMs) are widely used in many sub-fields of natural
language processing (NLP) and generally known as excellent few-shot learners with task …