343 citations · 494 across the 18 of their papers we have counts for
9 papers · 1 filter
Learning Neural Models for Natural Language Processing in the Face of Distributional Shift
Paul Michel
The dominating NLP paradigm of training a strong neural predictor to perform one task on a specific dataset has led to state-of-the-art performance in a variety of applications (eg…
Findings of the First Shared Task on Machine Translation Robustness
Xian Li, Paul Michel, Antonios Anastasopoulos +7
We share the findings of the first shared task on improving robustness of Machine Translation (MT). The task provides a testbed representing challenges facing MT models deployed in…
Are Sixteen Heads Really Better than One?
Paul Michel, Omer Levy, Graham Neubig
Attention is a powerful and ubiquitous mechanism for allowing neural models to focus on particular salient pieces of information by taking their weighted average when making predic…
On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models
Paul Michel, Xian Li, Graham Neubig +1
Adversarial examples --- perturbations to the input of a model that elicit large changes in the output --- have been shown to be an effective way of assessing the robustness of seq…
compare-mt: A Tool for Holistic Comparison of Language Generation Systems
Graham Neubig, Zi-Yi Dou, Junjie Hu +4
In this paper, we describe compare-mt, a tool for holistic analysis and comparison of the results of systems for language generation tasks such as machine translation. The main goa…
MTNT: A Testbed for Machine Translation of Noisy Text
Paul Michel, Graham Neubig
Noisy or non-standard input text can cause disastrous mistranslations in most modern Machine Translation (MT) systems, and there has been growing research interest in creating nois…
Extreme Adaptation for Personalized Neural Machine Translation
Paul Michel, Graham Neubig
Every person speaks or writes their own flavor of their native language, influenced by a number of factors: the content they tend to talk about, their gender, their social status,…
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations
Paul Michel, Abhilasha Ravichander, Shruti Rijhwani
We investigate the pertinence of methods from algebraic topology for text data analysis. These methods enable the development of mathematically-principled isometric-invariant mappi…
Blind phoneme segmentation with temporal prediction errors
Paul Michel, Okko Räsänen, Roland Thiollière +1
Phonemic segmentation of speech is a critical step of speech recognition systems. We propose a novel unsupervised algorithm based on sequence prediction models such as Markov chain…