arXiv · 2404.15848
Detecting Conceptual Abstraction in LLMs
Abstract
We present a novel approach to detecting noun abstraction within a large language model (LLM). Starting from a psychologically motivated set of noun pairs in taxonomic relationships, we instantiate surface patterns indicating hypernymy and analyze the attention matrices produced by BERT. We compare the results to two sets of counterfactuals and show that we can detect hypernymy in the abstraction mechanism, which cannot solely be related to the distributional similarity of noun pairs. Our findings are a first step towards the explainability of conceptual abstraction in LLMs.
Explore related subjects
Keep this discovery
Michaela Regneri, Alhassan Abdelhalim, Sören Laue. 2024-04-24. Detecting Conceptual Abstraction in LLMs. https://arxiv.org/abs/2404.15848
Cite the original work for its findings. Save a collection to share your selection of sources.