Research demonstrates how Audio Large Language Models (Audio LLMs) can be optimized for complex auditory cognitive tasks through test-time compute scaling.

• Extends LLM capabilities beyond text to speech processing challenges
• Focuses on real-world auditory tasks like audio comprehension and listening recall
• Introduces methods to enhance audio understanding without retraining
• Explores practical applications in assistive listening technologies

For medical applications, this research enables development of advanced hearing assistance devices with improved comprehension capabilities in complex environments, benefiting patients with hearing difficulties.

Scaling Auditory Cognition via Test-Time Compute in Audio Language Models