In the meantime, a wide variety of terminologies, motivations, approaches, and evaluation
criteria have been developed within the research field of explainable artificial intelligence …

Transformers have supplanted recurrent models in a large number of NLP tasks. However,
the differences in their abilities to model different syntactic properties remain largely …

The interpretability of deep learning models has raised extended attention these years. It will
be beneficial if we can learn an interpretable structure from deep learning models. In this …

Data samples collected for training machine learning models are typically assumed to be
independent and identically distributed (iid). Recent research has demonstrated that this …

Industrial control system (ICS) protocols face the threat of adversaries launching cyber-
physical attacks against protocol endpoints. Vulnerability discovery approaches such as …

We investigate a finer-grained understanding of the characteristics of particular deterministic
finite automata (DFA). Specifically, we study and identify the transitions of a DFA that are …