The choice of token vocabulary affects the performance of machine translation. This paper
aims to figure out what is a good vocabulary and whether one can find the optimal …

Directed evolution, a strategy for protein engineering, optimizes protein properties (ie,
fitness) by a rigorous and resource-intensive process of screening or selecting among a vast …

Abstract Language complexity is an intriguing phenomenon argued to play an important role
in both language learning and processing. The need to compare languages with regard to …

Molecule generation is central to a variety of applications. Current attention has been paid to
approaching the generation task as subgraph prediction and assembling. Nevertheless …

Morphological complexity is widely believed to increase with sociolinguistic isolation, and to
decrease with language spreads and absorption of L2 adult learner populations. However …

Abstract Machine Translation (MT) has come a long way in recent years, but it still suffers
from data scarcity issue due to lack of parallel corpora for low (or sometimes zero) resource …

This research focuses on classifying translated and non-translated Chinese texts by
analyzing syntactic rule features, using an integrated approach of machine learning and …

Many computational linguistic methods have been proposed to study the information content
of languages. We consider two interesting research questions: 1) how is information …

There is high hope that corpus-based approaches to language complexity will contribute to
explaining linguistic diversity. Several complexity indices have consequently been proposed …

Molecular graph generation is a fundamental but challenging task in various applications
such as drug discovery and material science, which requires generating valid molecules …