3 papers
cs.CL2026
Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs
Carolina Camassa, Derek Shiller
Language models are trained to follow instructions, but they are also powerful pattern completers. What happens when these two objectives conflict? We construct conversations in wh…
cs.CL2025
Prompting for Policy: Forecasting Macroeconomic Scenarios with Synthetic LLM Personas
Giulia Iadisernia, Carolina Camassa
We evaluate whether persona-based prompting improves Large Language Model (LLM) performance on macroeconomic forecasting tasks. Using 2,368 economics-related personas from the Pers…
cs.CY2025
Chat Bankman-Fried: an Exploration of LLM Alignment in Finance
Claudia Biancotti, Carolina Camassa, Andrea Coletta +2
Advancements in large language models (LLMs) have renewed concerns about AI alignment - the consistency between human and AI goals and values. As various jurisdictions enact legisl…