An abundance of datasets exist for training and evaluating models on the...
Like people, LLMs do not always generate the best text for a given gener...
Language models have steadily increased in size over the past few years....
Instruction tuning is an emergent paradigm in NLP wherein natural langua...
Target-guided response generation enables dialogue systems to smoothly
t...
Fact-checking is an essential tool to mitigate the spread of misinformat...
Open-domain neural dialogue models have achieved high performance in res...
The advent of contextual word embeddings – representations of words whic...
Large-scale models for learning fixed-dimensional cross-lingual sentence...
Dialogue systems pretrained with large language models generate locally
...
This paper develops the equilibrium equations describing the flexoelectr...
Interactive search sessions often contain multiple queries, where the us...
Recent advances in cross-lingual word embeddings have primarily relied o...
The aim of this paper is to mitigate the shortcomings of automatic evalu...
We study the problem of generating interesting endings for stories. Neur...
Pre-trained word vectors are ubiquitous in Natural Language Processing
a...
Learning to rank is an important problem in machine learning and recomme...
Distributed word representations, or word vectors, have recently been ap...
We introduce models for saliency prediction for mobile user interfaces. ...
The recent tremendous success of unsupervised word embeddings in a multi...