5 papers
Language Distances are Practical for Equitable Cross-Lingual Transfer
York Hay Ng, Razan Ahsan Rifandi, Aditya Khan +1
Cross-lingual transfer is strongly conditional on how the source language is chosen, but it is impractical to determine the best candidate source for every target language, especia…
Dynamic Meta-Metrics: Source-Sentence Conditioned Weighting for MT Evaluation
Luke Zhang, Justin Vasselli, Aditya Khan +2
We propose Dynamic Meta-Metrics (DMM), a framework for machine translation evaluation that learns source-sentence conditioned combinations of existing metrics. Rather than relying…
\textsc{CantoNLU}: A benchmark for Cantonese natural language understanding
Junghyun Min, York Hay Ng, Sophia Chan +2
Cantonese, although spoken by millions, remains under-resourced due to policy and diglossia. To address this scarcity of evaluation frameworks for Cantonese, we introduce \textsc{\…
Simple Additions, Substantial Gains: Expanding Scripts, Languages, and Lineage Coverage in URIEL+
Mason Shipton, York Hay Ng, Aditya Khan +4
The URIEL+ linguistic knowledge base supports multilingual research by encoding languages through geographic, genetic, and typological vectors. However, data sparsity (e.g. missing…
Modality Matching Matters: Calibrating Language Distances for Cross-Lingual Transfer in URIEL+
York Hay Ng, Aditya Khan, Xiang Lu +5
Existing linguistic knowledge bases such as URIEL+ provide valuable geographic, genetic and typological distances for cross-lingual transfer but suffer from two key limitations. Fi…