Nudging Hidden States: Training-Free Model Steering for Chain-of-Thought Reasoning in Large Audio-Language Models

Researchers developed training-free model steering techniques to improve reasoning in large audio-language models (LALMs) through chain-of-thought prompting. The approach achieved up to 4.4% accuracy gains and demonstrated cross-modal transfer where text-derived steering vectors can effectively guide speech-based reasoning.