2026
AR&D: A Framework for Retrieving and Describing Concepts for Interpreting AudioLLMs
ICASSP 2026oral
Despite strong performance in audio perception tasks, large audio-language models (AudioLLMs) remain opaque to interpretation. A major factor behind this lack of interpretability is that individual neurons in these models frequently activate in response to several unrelated concepts. We introduce th…