Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …

Abstract Human-Agent Interaction is at the forefront of rapid development, with integrating
deep learning techniques into natural language processing representing significant …

Artificial intelligence (AI) has made remarkable progress across various domains, with large
language models like ChatGPT gaining substantial attention for their human-like text …

Implementing human-level reasoning about action effects is an important competence for a
cognitive agent: given precondition and action descriptions, a system should be able to infer …

In this paper we analyse the issue of reference using spatial language and examine how the
polysemy exhibited by spatial prepositions can be incorporated into semantic models for …

In mobile edge computing (MEC), quality of service (QoS) is closely related to optimizing
service placement strategies, which is crucial to providing efficient services that meet user …

Grounded language processing is a crucial component in many artificial intelligence
systems, as it allows agents to communicate about their physical surroundings. State-of-the …

Spatial reasoning plays a vital role in both human cognition and machine intelligence,
prompting new research into language models'(LMs) capabilities in this regard. However …

This article presents a new machine unlearning approach that utilizes multiple Generative
Adversarial Network (GAN) based models. The proposed method comprises two phases: i) …

Artificial intelligence is to teach machines to take actions like humans. To achieve intelligent
teaching, the machine learning community becomes to think about a promising topic named …