How does BERT's attention change when you fine-tune? An analysis methodology and a case study in negation scope

ACL 2020 Yiyun ZhaoSteven Bethard

Large pretrained language models like BERT, after fine-tuning to a downstream task, have achieved high performance on a variety of NLP problems. Yet explaining their decisions is difficult despite recent work probing their internal representations... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper