research
∙
07/28/2023
Uncertainty in Natural Language Generation: From Theory to Applications
Recent advances of powerful Language Models have allowed Natural Languag...
share
research
∙
05/19/2023
What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability
In Natural Language Generation (NLG) tasks, for any input, multiple comm...
research
∙
04/13/2023
VISION DIFFMASK: Faithful Interpretation of Vision Transformers with Differentiable Patch Masking
The lack of interpretability of the Vision Transformer may hinder its us...
research
∙
10/28/2022
Stop Measuring Calibration When Humans Disagree
Calibration is a popular framework to evaluate whether a classifier know...
research
∙
04/06/2022
Statistical Model Criticism of Variational Auto-Encoders
We propose a framework for the statistical evaluation of variational aut...
research
∙
09/08/2021
Highly Parallel Autoregressive Entity Linking with Discriminative Correction
Generative approaches have been recently shown to be effective for both ...
research
∙
08/10/2021
Sampling-Based Minimum Bayes Risk Decoding for Neural Machine Translation
In neural machine translation (NMT), we search for the mode of the model...
research
∙
08/05/2021
Sparse Communication via Mixed Distributions
Neural networks and other machine learning models compute continuous rep...
research
∙
04/16/2021
Editing Factual Knowledge in Language Models
The factual knowledge acquired during pretraining and stored in the para...
research
∙
10/24/2020
Disease Normalization with Graph Embeddings
The detection and normalization of diseases in biomedical texts are key ...
research
∙
07/03/2020
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity
Training neural network models with discrete (categorical or structured)...
research
∙
06/11/2020
Latent Transformations for Discrete-Data Normalising Flows
Normalising flows (NFs) for discrete data are challenging because parame...
research
∙
06/08/2020
The Power Spherical distribution
There is a growing interest in probabilistic models defined in hyper-sph...
research
∙
05/20/2020
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation
Recent studies have revealed a number of pathologies of neural machine t...
research
∙
04/30/2020
How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking
Attribution methods assess the contribution of inputs (e.g., words) to t...
research
∙
10/30/2019
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation
Translation into morphologically-rich languages challenges neural machin...
research
∙
05/20/2019
Interpretable Neural Predictions with Differentiable Binary Variables
The success of neural networks comes hand in hand with a desire for more...
research
∙
04/17/2019
Effective Estimation of Deep Generative Language Models
Advances in variational inference enable parameterisation of probabilist...
research
∙
04/09/2019
Block Neural Autoregressive Flow
Normalising flows (NFS) map two density functions via a differentiable b...
research
∙
01/18/2019
Modeling Latent Sentence Structure in Neural Machine Translation
Recently it was shown that linguistic structure predicted by a supervise...
research
∙
11/01/2018
Latent Visual Cues for Neural Machine Translation
In this work, we propose to model the interaction between visual and tex...
research
∙
08/29/2018
Question Answering by Reasoning Across Documents with Graph Convolutional Networks
Most research in reading comprehension has focused on answering question...
research
∙
07/27/2018
Auto-Encoding Variational Neural Machine Translation
We present a deep generative model of bilingual sentence pairs. The mode...
research
∙
05/28/2018
A Stochastic Decoder for Neural Machine Translation
The process of translation is ambiguous, in that there are typically man...
research
∙
02/16/2018
Deep Generative Model for Joint Alignment and Word Representation
This work exploits translation data as a source of semantically relevant...
research
∙
04/15/2017
Graph Convolutional Encoders for Syntax-aware Neural Machine Translation
We present a simple and effective approach to incorporating syntactic st...
research
∙
09/13/2015
