A key feature of out-of-distribution (OOD) detection is to exploit a tra...
The evaluation of natural language processing (NLP) systems is crucial f...
Large-scale multilingual machine translation systems have demonstrated
r...
As language models grow ever larger, the need for large-scale high-quali...
Out-of-distribution (OOD) detection is a rapidly growing field due to ne...
Neural machine translation (NMT) has become the de-facto standard in
rea...
As more and more conversational and translation systems are deployed in
...
Deep learning methods have boosted the adoption of NLP systems in real-l...
Automatic evaluation metrics capable of replacing human judgments are
cr...
Research on Automatic Story Generation (ASG) relies heavily on human and...
When working with textual data, a natural application of disentangled
re...
Mutual Information (MI) has been widely used as a loss regularizer for
t...
In Machine Learning, a benchmark refers to an ensemble of datasets assoc...
Assessing the quality of natural language generation systems through hum...
Sequence-to-sequence neural networks have been widely used in language-b...
Multimodal sentiment analysis is a trending area of research, and the
mu...
Spoken dialog systems need to be able to handle both multiple languages ...
A new metric to evaluate text generation based on deep
contextualized e...
Learning disentangled representations of textual data is essential for m...
While being an essential component of spoken language, fillers (e.g."um"...
Sequence labelling tasks like Dialog Act and Emotion/Sentiment identific...
The dominant approaches to text representation in natural language rely ...
The task of predicting dialog acts (DA) based on conversational dialog i...
The task of predicting dialog acts (DA) based on conversational dialog i...
The task of predicting fine grained user opinion based on spontaneous sp...
The majority of current systems for end-to-end dialog generation focus o...