Auditing Asset-Specific Preferences in Financial Large Language Models: Evidence from Bitcoin Representations and Portfolio Allocation
arXiv:2606.02528v2 Announce Type: replace-cross Abstract: Large language models now power robo-advisors and trading agents, yet whether they carry built-in biases toward specific assets is largely untested. We ask three questions: do LLMs systematically prefer certain financial instruments; can an internal representation with causal leverage over those preferences be identified; and does that representation affect downstream financial decisions? We develop a three-level audit protocol and apply
Record details
Published: 16 July 2026
Source: arXiv cs.CY
Category: Research
Topics: Agents & autonomy · Transparency
Retrieved: 16 July 2026
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ethics.ai (16 July 2026), “Auditing Asset-Specific Preferences in Financial Large Language Models: Evidence from Bitcoin Representations and Portfolio Allocation,” evidence record 10554, https://ethics.ai/record/10554 (originally published by arXiv cs.CY).
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