Abstract. We present an automated, system-internal evaluation technique for linguistic representations in a large-scale, multilingual MT system.

Abstract. We present an automated, system-internal evaluation technique for linguistic representations in a large-scale, multilingual MT system.

We present an automated, system-internal evaluation technique for linguistic representations in a large-scale, multilingual MT system.

Jan 1, 2001 � We present an automated, system-internal evaluation technique for linguistic representations in a large-scale, multilingual MT system.

We present a machine learning approach to evaluating the well-formedness of output of a machine translation system, using classifiers that learn to distinguish�...

This workshop aims to bridge this gap by defining, evaluating, and understanding the implications of representational alignment among biological & artificial�...

Aug 24, 2023 � Natural language processing (NLP) aims to build linguistic-specific programs for machines to understand and use human languages.

Representation learning enables us to automati- cally extract generic feature representations from a dataset to solve another machine learning task. Re- cently,�...

This paper investigates the quality of vector representations learned at different layers of NMT encoders and finds that higher layers are better at learning�...

Dec 8, 2022 � This workshop aims to bring together the research community consisting of scientists studying different aspects in multilingual representation learning.