230 citations · 311 across the 33 of their papers we have counts for
6 papers · 1 filter
Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark
Stephen Mayhew, Terra Blevins, Shuheng Liu +10
We introduce Universal NER (UNER), an open, community-driven project to develop gold-standard NER benchmarks in many languages. The overarching goal of UNER is to provide high-qual…
That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?
Jaechan Lee, Alisa Liu, Orevaoghene Ahia +2
The translation of ambiguous text presents a challenge for translation systems, as it requires using the surrounding context to disambiguate the intended meaning as much as possibl…
BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer
Akari Asai, Sneha Kudugunta, Xinyan Velocity Yu +6
Despite remarkable advancements in few-shot generalization in natural language processing, most models are developed and evaluated primarily in English. To facilitate research on f…
Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models
Orevaoghene Ahia, Sachin Kumar, Hila Gonen +4
Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of the…
Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation
Marjan Ghazvininejad, Hila Gonen, Luke Zettlemoyer
Large language models (LLMs) demonstrate remarkable machine translation (MT) abilities via prompting, even though they were not explicitly trained for this task. However, even give…
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
Davis Liang, Hila Gonen, Yuning Mao +5
Large multilingual language models typically rely on a single vocabulary shared across 100+ languages. As these models have increased in parameter count and depth, vocabulary size…