152 citations · 162 across the 4 of their papers we have counts for
6 papers
Low-Complexity Probing via Finding Subnetworks
Steven Cao, Victor Sanh, Alexander M. Rush
The dominant approach in probing neural networks for linguistic properties is to train a new shallow multi-layer perceptron (MLP) on top of the model's internal representations. Th…
Unsupervised Parsing via Constituency Tests
Steven Cao, Nikita Kitaev, Dan Klein
We propose a method for unsupervised parsing based on the linguistic notion of a constituency test. One type of constituency test involves modifying the sentence via some transform…
CoVer: Collaborative Light-Node-Only Verification and Data Availability for Blockchains
Steven Cao, Swanand Kadhe, Kannan Ramchandran
Validating a blockchain incurs heavy computation, communication, and storage costs. As a result, clients with limited resources, called light nodes, cannot verify transactions inde…
Multilingual Alignment of Contextual Word Representations
Steven Cao, Nikita Kitaev, Dan Klein
We propose procedures for evaluating and strengthening contextual embedding alignment and show that they are useful in analyzing and improving multilingual BERT. In particular, aft…
Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction
Hongjiang Wei, Steven Cao, Yuyao Zhang +4
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing step…
Multilingual Constituency Parsing with Self-Attention and Pre-Training
Nikita Kitaev, Steven Cao, Dan Klein
We show that constituency parsing benefits from unsupervised pre-training across a variety of languages and a range of pre-training conditions. We first compare the benefits of no…