Kris Cao

Mind the Gap: Assessing Temporal Generalization in Neural Language Models

2021 · arXiv (Cornell University)

Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contrasts with the current static language modelling …

What is the best recipe for character-level encoder-only modelling?

2023 · arXiv (Cornell University)

This paper aims to benchmark recent progress in language understanding models that output contextualised representations at the character level. Many such modelling architectures and methods to train those architectures have been proposed, but it is …

A Joint Model for Word Embedding and Word Morphology

2016

This paper presents a joint model for performing unsupervised morphological analysis on words, and learning a character-level composition function from morphemes to word embeddings. Our model splits individual words into segments, and weights each segment …