TopEx: Topic-based Explanations for Model Comparison
Computation and Language
2023-06-05 v2
Abstract
Meaningfully comparing language models is challenging with current explanation methods. Current explanations are overwhelming for humans due to large vocabularies or incomparable across models. We present TopEx, an explanation method that enables a level playing field for comparing language models via model-agnostic topics. We demonstrate how TopEx can identify similarities and differences between DistilRoBERTa and GPT-2 on a variety of NLP tasks.
Cite
@article{arxiv.2306.00976,
title = {TopEx: Topic-based Explanations for Model Comparison},
author = {Shreya Havaldar and Adam Stein and Eric Wong and Lyle Ungar},
journal= {arXiv preprint arXiv:2306.00976},
year = {2023}
}
Comments
Accepted to ICLR 2023, Tiny Papers Track