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Structured Persona Extraction for LLM-Based Digital Twins

The study investigates how structuring persona information affects accuracy of LLM-based digital twins. It argues that structural organization, not information volume, is the key bottleneck. Unstructured summaries are compared with structured persona representations.

Why it matters

Findings help improve methods of building digital twins of individuals for predicting behavior in novel situations.

Relevant to DT products

Original headline
Beyond Raw Transcripts: Structured Persona Extraction for LLM-Based Digital Twins
Read the original: arXiv — Computers and Society (cs.CY)

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