  While large language models (LLMs) have demonstrated strong capability in
structured prediction tasks such as semantic parsing, few amounts of research
have explored the underlying mechanisms of their success. Our work studies
different methods for explaining an LLM-based semantic parser and qualitatively
discusses the explained model behaviors, hoping to inspire future research
toward better understanding them.

Computation and Language;Artificial Intelligence