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

565 citations · 1.3k across the 96 of their papers we have counts for

collaborators
Showing 2022Show all

12 papers · 1 filter

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…

physics.ins-det2022★ 12 cited

Transfer Learning Application of Self-supervised Learning in ARPES

Sandy Adhitia Ekahana, Genta Indra Winata, Y. Soh +3

Recent development in angle-resolved photoemission spectroscopy (ARPES) technique involves spatially resolving samples while maintaining the high-resolution feature of momentum spa…

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…

cs.CL2022★ 565 cited

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…

cs.CL2022★ 8 cited

NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages

Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya +11

Natural language processing (NLP) has a significant impact on society via technologies such as machine translation and search engines. Despite its success, NLP technology is only w…

cs.CL2022★ 13 cited

One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia

Alham Fikri Aji, Genta Indra Winata, Fajri Koto +9

NLP research is impeded by a lack of resources and awareness of the challenges presented by underrepresented languages and dialects. Focusing on the languages spoken in Indonesia,…

cs.CL2022

A Comparative Study on Language Models for Task-Oriented Dialogue Systems

Vinsen Marselino Andreas, Genta Indra Winata, Ayu Purwarianti

The recent development of language models has shown promising results by achieving state-of-the-art performance on various natural language tasks by fine-tuning pretrained models.…

cs.CL2022★ 3 cited

CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition

Wenliang Dai, Samuel Cahyawijaya, Tiezheng Yu +10

With the rise of deep learning and intelligent vehicle, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-car…