The challenge of efficiently determining a user's preferences through natural language dialogues, specifically in the context of conversational recommender systems, is a focus of recent research. Traditional methods require users to rate or compare options, but this approach fails when the user is unfamiliar with the majority of potential choices. Solving this problem through Large…
Continual learning (CL), the capability of systems to adapt over time without losing prior knowledge, presents a significant challenge. Neural networks, while adept at processing large amounts of data, can often suffer from catastrophic forgetting, when learning new information may erase what was previously learned. This becomes extremely problematic in scenarios with limited data retention…
Physics, often perceived as an abstract and challenging field, covers fundamental aspects of the universe which can intimidate learners due to intricate mathematical formulations. To make physics more relatable, the field of Visual Intuitive Physics seeks to transform these complexities into accessible visual experiences through the use of visual aids and intuitive methodologies.
Visualization in physics…
Code interpreters have become important tools in the rapidly developing field of Artificial Intelligence (AI) as they enable AI models to execute code designed for specific problems, thus unlocking more advanced problem-solving capabilities. Enabling AI agents to run AI-generated code safely without compromising security and data integrity is one of the key challenges faced by…