On the Tip of the Tongue: Analyzing Conceptual Representation in Large Language Models with Reverse-Dictionary Probe

arXiv:2402.14404v1 Announce Type: new
Abstract: Probing and enhancing large language models' reasoning capacity remains a crucial open question. Here we re-purpose the reverse dictionary task as a case study to probe LLMs' capacity for conceptual inference. We use in-context learning to guide the models to generate the term for an object concept implied in a linguistic description. Models robustly achieve high accuracy in this task, and their representation space encodes information about object categories and fine-grained features. Further experiments suggest …

abstract arxiv capacity case case study context cs.ai cs.cl dictionary guide in-context learning inference language language models large language large language models llms probe question reasoning representation study type