minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models


We present $\texttt{minicons}$, an open source library that provides a standard API for researchers interested in conducting behavioral and representational analyses of transformer-based language models (LMs). Specifically, minicons enables researchers to apply analysis methods at two levels: (1) at the prediction level – by providing functions to efficiently extract word/sentence level probabilities; and (2) at the representational level – by also facilitating efficient extraction of word/phrase level vectors from one or more layers. In this paper, we describe the library and apply it to two motivating case studies: One focusing on the learning dynamics of the BERT architecture on relative grammatical judgments, and the other on benchmarking 23 different LMs on zero-shot abductive reasoning. minicons is available at this url.

In arxiv Preprint
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Kanishka Misra
Kanishka Misra
PhD Candidate

My research interests include Natural Language Processing, Cognitive Science, and Deep Learning.