activity
20202022
most citedData Augmentation for Sign Language Gloss Translation

5 citations · 8 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20223 cited

Interpreting Language Models with Contrastive Explanations

Kayo Yin, Graham Neubig

Model interpretability methods are often used to explain NLP model decisions on tasks such as text classification, where the output space is relatively small. However, when applied…

cs.CL2021

When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection

Aditi Chaudhary, Kayo Yin, Antonios Anastasopoulos +1

Learning fine-grained distinctions between vocabulary items is a key challenge in learning a new language. For example, the noun "wall" has different lexical manifestations in Span…

cs.CL2021

Measuring and Increasing Context Usage in Context-Aware Machine Translation

Patrick Fernandes, Kayo Yin, Graham Neubig +1

Recent work in neural machine translation has demonstrated both the necessity and feasibility of using inter-sentential context -- context from sentences other than those currently…

cs.CL20215 cited

Data Augmentation for Sign Language Gloss Translation

Amit Moryossef, Kayo Yin, Graham Neubig +1

Sign language translation (SLT) is often decomposed into video-to-gloss recognition and gloss-to-text translation, where a gloss is a sequence of transcribed spoken-language words…

cs.CL2021

Do Context-Aware Translation Models Pay the Right Attention?

Kayo Yin, Patrick Fernandes, Danish Pruthi +3

Context-aware machine translation models are designed to leverage contextual information, but often fail to do so. As a result, they inaccurately disambiguate pronouns and polysemo…

cs.CL2021

Including Signed Languages in Natural Language Processing

Kayo Yin, Amit Moryossef, Julie Hochgesang +2

Signed languages are the primary means of communication for many deaf and hard of hearing individuals. Since signed languages exhibit all the fundamental linguistic properties of n…