TopEx: Topic-based Explanations for Model Comparison
Autor: | Havaldar, Shreya, Stein, Adam, Wong, Eric, Ungar, Lyle |
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Rok vydání: | 2023 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | 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. Comment: Accepted to ICLR 2023, Tiny Papers Track |
Databáze: | arXiv |
Externí odkaz: |