Abstract Model robustness and spurious correlations have received increasing attention in the NLP community, both in methods and evaluation. The term “spurious correlation” is overloaded though and can refer to any undesirable shortcuts learned by[...]

Abstract Recursive calls over recursive data are widely useful for generating probability distributions, and probabilistic programming allows computations over these distributions to be expressed in a modular and intuitive way. Exact inference is also useful,[...]

Abstract Modern learning architectures for natural language processing have been very successful in incorporating a huge amount of texts into their parameters. However, by and large, such models store and use knowledge in distributed and[...]