70 citations · 75 across the 5 of their papers we have counts for
5 papers
Learning Modulo Theories
Matt Fredrikson, Kaiji Lu, Saranya Vijayakumar +3
Recent techniques that integrate \emph{solver layers} into Deep Neural Networks (DNNs) have shown promise in bridging a long-standing gap between inductive learning and symbolic re…
Order-sensitive Shapley Values for Evaluating Conceptual Soundness of NLP Models
Kaiji Lu, Anupam Datta
Previous works show that deep NLP models are not always conceptually sound: they do not always learn the correct linguistic concepts. Specifically, they can be insensitive to word…
Influence Patterns for Explaining Information Flow in BERT
Kaiji Lu, Zifan Wang, Piotr Mardziel +1
While attention is all you need may be proving true, we do not know why: attention-based transformer models such as BERT are superior but how information flows from input tokens to…
Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models
Kaiji Lu, Piotr Mardziel, Klas Leino +2
LSTM-based recurrent neural networks are the state-of-the-art for many natural language processing (NLP) tasks. Despite their performance, it is unclear whether, or how, LSTMs lear…
Gender Bias in Neural Natural Language Processing
Kaiji Lu, Piotr Mardziel, Fangjing Wu +2
We examine whether neural natural language processing (NLP) systems reflect historical biases in training data. We define a general benchmark to quantify gender bias in a variety o…