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
Characterizing the Role of Similarity in the Property Inferences of Language Models
Juan Diego Rodriguez, Aaron Mueller, Kanishka Misra
Hierarchical mixtures of Unigram models for short text clustering: the role of Beta-Liouville priors
Massimo Bilancia, Samuele Magro
On the Role of Depth and Looping for In-Context Learning with Task Diversity
Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar