In the past few years, the emergence of pre-training models has brought uni-modal fields
such as computer vision (CV) and natural language processing (NLP) to a new era …

Explainable NLP (ExNLP) has increasingly focused on collecting human-annotated textual
explanations. These explanations are used downstream in three ways: as data …

Trust is a central component of the interaction between people and AI, in that'incorrect'levels
of trust may cause misuse, abuse or disuse of the technology. But what, precisely, is the …

Foundation models have received much attention due to their effectiveness across a broad
range of downstream applications. Though there is a big convergence in terms of …

Self-rationalization models that predict task labels and generate free-text elaborations for
their predictions could enable more intuitive interaction with NLP systems. These models …

Natural language explanation (NLE) models aim at explaining the decision-making process
of a black box system via generating natural language sentences which are human-friendly …

Recently, there has been an increasing number of efforts to introduce models capable of
generating natural language explanations (NLEs) for their predictions on vision-language …

Recent advancements in artificial intelligence (AI) technology have raised concerns about
the ethical, moral, and legal safeguards. There is a pressing need to improve metrics for …

Despite the fact that Artificial Intelligence (AI) has boosted the achievement of remarkable
results across numerous data analysis tasks, however, this is typically accompanied by a …

Following the success of Large Language Models (LLMs), Large Multimodal Models
(LMMs), such as the Flamingo model and its subsequent competitors, have started to …