Integral Role
Research on the "role" of various components in complex systems focuses on understanding their contributions to overall system performance and behavior. Current investigations span diverse fields, examining the impact of factors like data embedding strategies in quantum computing, prompt engineering in large language models, and architectural choices in deep learning for improved generalization and efficiency. These studies are crucial for optimizing existing systems and developing new ones, with implications ranging from enhancing AI safety and healthcare applications to improving manufacturing processes and scientific discovery.
Papers
Salespeople vs SalesBot: Exploring the Role of Educational Value in Conversational Recommender Systems
Lidiya Murakhovs'ka, Philippe Laban, Tian Xie, Caiming Xiong, Chien-Sheng Wu
Understanding the Role of Input Token Characters in Language Models: How Does Information Loss Affect Performance?
Ahmed Alajrami, Katerina Margatina, Nikolaos Aletras
ML4EJ: Decoding the Role of Urban Features in Shaping Environmental Injustice Using Interpretable Machine Learning
Yu-Hsuan Ho, Zhewei Liu, Cheng-Chun Lee, Ali Mostafavi
Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advice
Max Schemmer, Andrea Bartos, Philipp Spitzer, Patrick Hemmer, Niklas Kühl, Jonas Liebschner, Gerhard Satzger