most citedNusaCrowd: A Call for Open and Reproducible NLP Research in Indonesian Languages

4 citations · 11 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2023

IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems

Muhammad Dehan Al Kautsar, Rahmah Khoirussyifa' Nurdini, Samuel Cahyawijaya +2

Task-oriented dialogue (ToD) systems have been mostly created for high-resource languages, such as English and Chinese. However, there is a need to develop ToD systems for other re…

cs.CL2023

NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages

Samuel Cahyawijaya, Holy Lovenia, Fajri Koto +15

Democratizing access to natural language processing (NLP) technology is crucial, especially for underrepresented and extremely low-resource languages. Previous research has focused…

cs.CL2023

On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research

Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Alham Fikri Aji +4

This evidence-based position paper critiques current research practices within the language model pre-training literature. Despite rapid recent progress afforded by increasingly be…

cs.CL20231 cited

Overcoming Catastrophic Forgetting in Massively Multilingual Continual Learning

Genta Indra Winata, Lingjue Xie, Karthik Radhakrishnan +5

Real-life multilingual systems should be able to efficiently incorporate new languages as data distributions fed to the system evolve and shift over time. To do this, systems need…

cs.CL20231 cited

Multi-lingual and Multi-cultural Figurative Language Understanding

Anubha Kabra, Emmy Liu, Simran Khanuja +6

Figurative language permeates human communication, but at the same time is relatively understudied in NLP. Datasets have been created in English to accelerate progress towards meas…

cs.CL20232 cited

GlobalBench: A Benchmark for Global Progress in Natural Language Processing

Yueqi Song, Catherine Cui, Simran Khanuja +9

Despite the major advances in NLP, significant disparities in NLP system performance across languages still exist. Arguably, these are due to uneven resource allocation and sub-opt…