Disease prediction based on patients' historical admission records is an essential task in the
medical field, but current predictive models often lack interpretability, which is a critical …

Imparting human-like commonsense to machines is a long-term goal in the artificial
intelligence community. To achieve this goal, constructing large-scale commonsense …

Scene graph generation aims to capture the semantic elements in images by modelling
objects and their relationships in a structured manner, which are essential for visual …

An increasingly prevalent problem for intelligent technologies is text safety, as uncontrolled
systems may generate recommendations to their users that lead to injury or life-threatening …

With the popularity of social media, rumors have become more prevalent than ever. The
impact of rumors is adverse, making their detection a growing concern and an indispensable …

Syllogism is a type of everyday reasoning. For instance, given that 'Avicenna wrote the
famous book the Canon of Medicine'and 'The Canon of Medicine has influenced modern …

Pre-trained Language Models (PTLMs) have been shown to perform well on natural
language tasks. Many prior works have leveraged structured commonsense present in the …

Enabling reinforcement learning (RL) agents to leverage a knowledge base while learning
from experience promises to advance RL in knowledge intensive domains. However, it has …

A primary goal of artificial intelligence is to understand human mental states. One direction
aims at emotionally coherent and empathetic machine systems. As emotion is often …

This thesis examines the ethical implications of artificial intelligence through the lens of
physical safety. It scrutinizes the various ways AI systems can instigate unsafe behavior in …