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
Understanding the Role of Optimization in Double Descent
Chris Yuhao Liu, Jeffrey Flanigan
On the Role of Edge Dependency in Graph Generative Models
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos Tsourakakis
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer
Elie Aljalbout, Felix Frank, Maximilian Karl, Patrick van der Smagt
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