120 citations · 469 across the 55 of their papers we have counts for
10 papers · 1 filter
AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages
Jiayi Wang, David Ifeoluwa Adelani, Sweta Agrawal +55
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, s…
Strings from the Library of Babel: Random Sampling as a Strong Baseline for Prompt Optimisation
Yao Lu, Jiayi Wang, Raphael Tang +2
Recent prompt optimisation approaches use the generative nature of language models to produce prompts -- even rivaling the performance of human-curated prompts. In this paper, we d…
AfroBench: How Good are Large Language Models on African Languages?
Jessica Ojo, Odunayo Ogundepo, Akintunde Oladipo +4
Large-scale multilingual evaluations, such as MEGA, often include only a handful of African languages due to the scarcity of high-quality evaluation data and the limited discoverab…
Using Natural Language Explanations to Improve Robustness of In-context Learning
Xuanli He, Yuxiang Wu, Oana-Maria Camburu +2
Recent studies demonstrated that large language models (LLMs) can excel in many tasks via in-context learning (ICL). However, recent works show that ICL-prompted models tend to pro…
Gender-specific Machine Translation with Large Language Models
Eduardo Sánchez, Pierre Andrews, Pontus Stenetorp +2
While machine translation (MT) systems have seen significant improvements, it is still common for translations to reflect societal biases, such as gender bias. Decoder-only Large L…
Improving Language Plasticity via Pretraining with Active Forgetting
Yihong Chen, Kelly Marchisio, Roberta Raileanu +4
Pretrained language models (PLMs) are today the primary model for natural language processing. Despite their impressive downstream performance, it can be difficult to apply PLMs to…