activity
20182026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 853 across the 78 of their papers we have counts for

collaborators
Showing 2022 · cs.CLShow all

11 papers · 2 filters

cs.CL2022★ 4 cited

The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges

Genta Indra Winata, Alham Fikri Aji, Zheng-Xin Yong +1

Code-Switching, a common phenomenon in written text and conversation, has been studied over decades by the natural language processing (NLP) research community. Initially, code-swi…

cs.CL2022★ 9 cited

NusaCrowd: Open Source Initiative for Indonesian NLP Resources

Samuel Cahyawijaya, Holy Lovenia, Alham Fikri Aji +44

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Thro…

cs.CL2022★ 2 cited

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

Zheng-Xin Yong, Hailey Schoelkopf, Niklas Muennighoff +12

The BLOOM model is a large publicly available multilingual language model, but its pretraining was limited to 46 languages. To extend the benefits of BLOOM to other languages witho…

cs.CL2022

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

BigScience Workshop, :, Teven Le Scao +391

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…

cs.CL2022★ 4 cited

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

Samuel Cahyawijaya, Alham Fikri Aji, Holy Lovenia +8

At the center of the underlying issues that halt Indonesian natural language processing (NLP) research advancement, we find data scarcity. Resources in Indonesian languages, especi…

cs.CL2022★ 3 cited

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74

Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…