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Rifki Afina Putri

6 accepted papers

2025

WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines

Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan, David Anugraha, Rifki Afina Putri, Wang Yutong +45
NAACL 2025long

Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate their understanding of such knowledge, we introduce WorldCuisines, a massive-scale benchmark for multilingual and multicul…

Cited by 11Source ↗PDF ↗code ↗Scholar ↗
2024

BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

Junho Myung, Nayeon Lee, Yi Zhou, Jiho Jin, Rifki Afina Putri, Dimosthenis Antypas +16
NeurIPS 2024poster

Large language models (LLMs) often lack culture-specific everyday knowledge, especially across diverse regions and non-English languages. Existing benchmarks for evaluating LLMs' cultural sensitivities are usually limited to a single language or online sources like Wikipedia, which may not reflect t…

Cited by 48Source ↗PDF ↗code ↗Scholar ↗
2024

Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and Sundanese

Rifki Afina Putri, Faiz Ghifari Haznitrama, Dea Adhista, Alice Oh
EMNLP 2024main

Large Language Models (LLMs) are increasingly being used to generate synthetic data for training and evaluating models. However, it is unclear whether they can generate a good quality of question answering (QA) dataset that incorporates knowledge and cultural nuance embedded in a language, especiall…

Cited by 11Source ↗PDF ↗code ↗Scholar ↗
2023

NusaCrowd: Open Source Initiative for Indonesian NLP Resources

Samuel Cahyawijaya, Holy Lovenia, Alham Fikri Aji, Genta Winata, Bryan Wilie, Fajri Koto +42
ACL 2023findings

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have brought together 137 datasets and 118 standardized data loaders. The quality of the dataset…

Cited by 1114Source ↗PDF ↗code ↗Scholar ↗
2023

Rethinking Annotation: Can Language Learners Contribute?

Haneul Yoo, Rifki Afina Putri, Changyoon Lee, Youngin Lee, So-Yeon Ahn, Dongyeop Kang +1
ACL 2023long

Researchers have traditionally recruited native speakers to provide annotations for the widely used benchmark datasets. But there are languages for which recruiting native speakers is difficult, and it would help to get learners of those languages to annotate the data. In this paper, we investigate…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗