Reference-based metrics that operate at the sentence level typically
out...
Large Language Models (LLMs) such as GPT-3 have emerged as general-purpo...
While Neural Machine Translation (NMT) represents the leading approach t...
Generative Pre-trained Transformer (GPT) models have shown remarkable
ca...
Large sequence to sequence models for tasks such as Neural Machine
Trans...
In this work, we present some recommendations on the evaluation of
state...
Memorization presents a challenge for several constrained Natural Langua...
Traditional machine translation (MT) metrics provide an average measure ...
End-to-end approaches for sequence tasks are becoming increasingly popul...
In this work, we study hallucinations in Neural Machine Translation (NMT...
We introduce GEM, a living benchmark for natural language Generation (NL...
We investigate two specific manifestations of compositionality in Neural...
Leveraging the visual modality effectively for Neural Machine Translatio...
Word embeddings have become a staple of several natural language process...
End-to-end acoustic-to-word speech recognition models have recently gain...
Word embeddings have become the basic building blocks for several natura...