SPEAR-MM: Selective Parameter Evaluation and Restoration via Model Merging for Efficient Financial LLM Adaptation

Key Points

• SPEAR-MM framework addresses catastrophic forgetting in financial LLMs during domain adaptation
• Method preserves general reasoning capabilities essential for customer interactions and complex financial analysis
• Uses selective parameter evaluation and model merging with layer-wise impact approximation

Implications

Enables more reliable financial LLM deployment by maintaining both domain expertise and general capabilities needed for customer-facing applications.

Action Required

Financial institutions should evaluate this approach for LLM implementations to avoid capability degradation during domain fine-tuning.