Bitcoin

Auditing Asset-Specific Preferences in Financial LLMs: Bitcoin Representations and Portfolio Allocation

Researchers develop a three-level audit protocol to test whether LLMs carry built-in biases toward specific financial assets, applying it to Bitcoin across eight frontier models. Using sparse autoencoder features in Gemma 3, they identify a dominant Bitcoin-selective internal feature whose amplification raises Bitcoin's portfolio share by 5.2 percentage points and suppression lowers it by 4.6 pp, even when 'Bitcoin' never appears in the prompt. The work introduces the concept of 'bounded behavioral leverage'—causal influence over outputs via identifiable internal representations—and frames the framework as a foundation for 'know-your-agent' (KYA) standards for autonomous financial agents.