215 citations · 516 across the 30 of their papers we have counts for
3 papers · 1 filter
RNN Architecture Learning with Sparse Regularization
Jesse Dodge, Roy Schwartz, Hao Peng +1
Neural models for NLP typically use large numbers of parameters to reach state-of-the-art performance, which can lead to excessive memory usage and increased runtime. We present a…
Show Your Work: Improved Reporting of Experimental Results
Jesse Dodge, Suchin Gururangan, Dallas Card +2
Research in natural language processing proceeds, in part, by demonstrating that new models achieve superior performance (e.g., accuracy) on held-out test data, compared to previou…
Green AI
Roy Schwartz, Jesse Dodge, Noah A. Smith +1
The computations required for deep learning research have been doubling every few months, resulting in an estimated 300,000x increase from 2012 to 2018 [2]. These computations have…