2 citations · 3 across the 12 of their papers we have counts for
5 papers · 1 filter
ChiKhaPo: A Large-Scale Multilingual Benchmark for Evaluating Lexical Comprehension and Generation in Large Language Models
Emily Chang, Niyati Bafna
Existing benchmarks for large language models (LLMs) are largely restricted to high- or mid-resource languages, and often evaluate performance on higher-order tasks in reasoning an…
How Important is `Perfect' English for Machine Translation Prompts?
Patrícia Schmidtová, Niyati Bafna, Seth Aycock +4
Large language models (LLMs) have achieved top results in recent machine translation evaluations, but they are also known to be sensitive to errors and perturbations in their promp…
LID Models are Actually Accent Classifiers: Implications and Solutions for LID on Accented Speech
Niyati Bafna, Matthew Wiesner
Prior research indicates that LID model performance significantly declines on accented speech; however, the specific causes, extent, and characterization of these errors remain und…
The Translation Barrier Hypothesis: Multilingual Generation with Large Language Models Suffers from Implicit Translation Failure
Niyati Bafna, Tianjian Li, Kenton Murray +4
Multilingual generation with large language models (LLMs) is often of poor quality for mid- to low-resource languages, but the causes for this are not well-understood. We first dem…
DialUp! Modeling the Language Continuum by Adapting Models to Dialects and Dialects to Models
Niyati Bafna, Emily Chang, Nathaniel R. Robinson +4
Most of the world's languages and dialects are low-resource, and lack support in mainstream machine translation (MT) models. However, many of them have a closely-related high-resou…