44 citations · 67 across the 24 of their papers we have counts for
7 papers · 2 filters
WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines
Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan +48
Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate th…
URIEL+: Enhancing Linguistic Inclusion and Usability in a Typological and Multilingual Knowledge Base
Aditya Khan, Mason Shipton, David Anugraha +5
URIEL is a knowledge base offering geographical, phylogenetic, and typological vector representations for 7970 languages. It includes distance measures between these vectors for 40…
ProxyLM: Predicting Language Model Performance on Multilingual Tasks via Proxy Models
David Anugraha, Genta Indra Winata, Chenyue Li +2
Performance prediction is a method to estimate the performance of Language Models (LMs) on various Natural Language Processing (NLP) tasks, mitigating computational costs associate…
IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models
David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime +24
Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource lang…
A Reproducibility Study on Quantifying Language Similarity: The Impact of Missing Values in the URIEL Knowledge Base
Hasti Toossi, Guo Qing Huai, Jinyu Liu +3
In the pursuit of supporting more languages around the world, tools that characterize properties of languages play a key role in expanding the existing multilingual NLP research. I…
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation
Tong Su, Xin Peng, Sarubi Thillainathan +3
Parameter-efficient fine-tuning (PEFT) methods are increasingly vital in adapting large-scale pre-trained language models for diverse tasks, offering a balance between adaptability…
Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity
Eric Khiu, Hasti Toossi, David Anugraha +6
Fine-tuning and testing a multilingual large language model is expensive and challenging for low-resource languages (LRLs). While previous studies have predicted the performance of…