Rifki Afina Putri
Rifki Afina Putri has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Question answering, Evaluation & benchmarks; often with Abinew Ali Ayele, Adam Nohejl, Alice Oh.
OpenAlex · ORCID · h-index 8 · 20 works · 129 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 255 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5394
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 3 worksBiochemistry, Genetics and Molecular Biology · 1 workMolecular Biology · 1 work
🧭 Topics 7Research subjects and languages the work is about.Language models & pretraining · 2 worksEvaluation & benchmarks · 2 worksQuestion answering · 2 worksReasoning · 1 workMultilingual & cross-lingual NLP · 1 workVision & language · 1 workLow-resource languages · 1 work
Works by year
2020s
Papers
- BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages (2024 · 152 citations)
Large language models often know little about ordinary daily life outside a few well-documented cultures. Facts like what people eat on birthdays or which sports pupils play rarely appear in web sources such as Wikipedia. Earlier cultural benchmarks were also mostly limited to one language or built from scraped… - WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines (2025 · 46 citations)
Vision Language Models (VLMs) often lack culture-specific knowledge, especially outside English and for underrepresented regions. - Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and Sundanese (2024 · 38 citations)
The paper asks whether large language models can produce commonsense question-answering data that reflects local culture in Indonesian and in Sundanese. - AnnoHID: LLM-Assisted Annotation Framework for Low-Resource Medical Texts (2026)
Training Medical Concept Normalization (MCN) systems requires annotated data that links everyday patient wording to standard clinical vocabularies.
All works
- BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and LanguagesConference on Neural Information Processing Systems (NeurIPS)Junho Myung, Nayeon Lee, Yi Zhou, et al.2024 · 152 citations
- NusaCrowd: Open Source Initiative for Indonesian NLP Resources ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetSamuel Cahyawijaya et al.2023 · 95 citations
- WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global CuisinesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan, et al.2025 · 46 citations
- Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and SundaneseConference on Empirical Methods in Natural Language Processing (EMNLP)Rifki Afina Putri, Faiz Ghifari Haznitrama, Dea Adhista, et al.2024 · 38 citations
- AnnoHID: LLM-Assisted Annotation Framework for Low-Resource Medical TextsAnnual Meeting of the Association for Computational Linguistics (ACL)Annisa Maulida Ningtyas, Guntur Budi Herwanto, Yunita Sari, et al.2026
Co-authors here
- Abinew Ali Ayele
- Adam Nohejl
- Alice Oh
- Carla Perez-Almendros
- David Anugraha
- Eunsu Kim
- Faiz Ghifari Haznitrama
- Frederikus Hudi
- Genta Indra Winata
- Jiho Jin
- Junho Myung
- Nayeon Lee
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2024
- Conference of the North American Chapter of the Association for Computational Linguistics (NAACL): NAACL 2025
- Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2024
- Findings of the Association for Computational Linguistics: ACL 2023
Cited by
Updated
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