5 papers
Near-Universal Multiplicative Updates for Nonnegative Einsum Factorization
John Hood, Aaron Schein
Despite the ubiquity of multiway data across scientific domains, there are few user-friendly tools that fit tailored nonnegative tensor factorizations. Researchers may use gradient…
Layers at Similar Depths Generate Similar Activations Across LLM Architectures
Christopher Wolfram, Aaron Schein
How do the latent spaces used by independently-trained LLMs relate to one another? We study the nearest neighbor relationships induced by activations at different layers of 24 open…
Modeling Latent Underdispersion with Discrete Order Statistics
Jimmy Lederman, Aaron Schein
The Poisson distribution is the default choice of likelihood for probabilistic models of count data. However, due to the equidispersion contraint of the Poisson, such models may ha…
Broad Spectrum Structure Discovery in Large-Scale Higher-Order Networks
John Hood, Caterina De Bacco, Aaron Schein
Complex systems are often driven by higher-order interactions among multiple units, naturally represented as hypergraphs. Understanding dependency structures within these hypergrap…
Linear Representations of Political Perspective Emerge in Large Language Models
Junsol Kim, James Evans, Aaron Schein
Large language models (LLMs) have demonstrated the ability to generate text that realistically reflects a range of different subjective human perspectives. This paper studies how L…