22 citations · 50 across the 7 of their papers we have counts for
18 papers
Stop Measuring Calibration When Humans Disagree
Joris Baan, Wilker Aziz, Barbara Plank +1
Calibration is a popular framework to evaluate whether a classifier knows when it does not know - i.e., its predictive probabilities are a good indication of how likely a predictio…
Statistical Model Criticism of Variational Auto-Encoders
Claartje Barkhof, Wilker Aziz
We propose a framework for the statistical evaluation of variational auto-encoders (VAEs) and test two instances of this framework in the context of modelling images of handwritten…
Highly Parallel Autoregressive Entity Linking with Discriminative Correction
Nicola De Cao, Wilker Aziz, Ivan Titov
Generative approaches have been recently shown to be effective for both Entity Disambiguation and Entity Linking (i.e., joint mention detection and disambiguation). However, the pr…
Editing Factual Knowledge in Language Models
Nicola De Cao, Wilker Aziz, Ivan Titov
The factual knowledge acquired during pre-training and stored in the parameters of Language Models (LMs) can be useful in downstream tasks (e.g., question answering or textual infe…
Disease Normalization with Graph Embeddings
Dhruba Pujary, Camilo Thorne, Wilker Aziz
The detection and normalization of diseases in biomedical texts are key biomedical natural language processing tasks. Disease names need not only be identified, but also normalized…
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity
Gonçalo M. Correia, Vlad Niculae, Wilker Aziz +1
Training neural network models with discrete (categorical or structured) latent variables can be computationally challenging, due to the need for marginalization over large or comb…