mode collapse 1political attitudes 1semantic similarity rating 1silicon sampling 1survey generation 1text embeddings 1
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cs.CY2026
Correcting Mode Collapse in Silicon Sampling with Semantic Similarity Rating
Oscar Heath, Rohan Alexander
The paper studies why large language models produce overly uniform survey answers (mode collapse) and proposes using semantic similarity ratings of text-only responses, mapped to n…
cs.CY2025
Prompting the Professoriate: A Qualitative Study of Instructor Perspectives on LLMs in Data Science Education
Ana Elisa Lopez-Miranda, Tiffany Timbers, Rohan Alexander
Large Language Models (LLMs) have shifted in just a few years from novelty to ubiquity, raising fundamental questions for data science education. Tasks once used to teach coding, w…
cs.CY2025
Limits to AI Growth: The Ecological and Social Consequences of Scaling
Eshta Bhardwaj, Rohan Alexander, Christoph Becker
The accelerating development and deployment of AI technologies depend on the continued ability to scale their infrastructure. This has implied increasing amounts of monetary invest…