Feb. 9, 2024, 5:47 a.m. | Angelica Chen Ravid Shwartz-Ziv Kyunghyun Cho Matthew L. Leavitt Naomi Saphra

cs.CL updates on arXiv.org arxiv.org

Most interpretability research in NLP focuses on understanding the behavior and features of a fully trained model. However, certain insights into model behavior may only be accessible by observing the trajectory of the training process. We present a case study of syntax acquisition in masked language models (MLMs) that demonstrates how analyzing the evolution of interpretable artifacts throughout training deepens our understanding of emergent behavior. In particular, we study Syntactic Attention Structure (SAS), a naturally emerging property of MLMs wherein …

acquisition behavior bias case case study cs.cl features insights interpretability interpretability research language loss model behavior nlp process research simplicity study syntax training trajectory transitions understanding

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