---
title: "Philippines — works of 2024: 3 papers, the most cited first"
description: "3 works of Philippines from 2024 in our library, the most cited first. Among them: SEACrowd: A Multilingual Multimodal Data Hub and…"
canonical: "https://research.elamur.ai/free/en/countries/philippines/year/2024/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/countries/philippines/year/2024/)

[home](https://md.research.elamur.ai/free/en/) / [countries](https://md.research.elamur.ai/free/en/countries/) / [Philippines](https://md.research.elamur.ai/free/en/countries/philippines/) / 2024

# Works of Philippines from 2024

3 works · the most cited first · [← Philippines](https://md.research.elamur.ai/free/en/countries/philippines/)

1. **[SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/lovenia-2024-seacrowd-multilingual-multimodal-data-hub/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar, et al.*2024 · 54 citations*
2. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
3. **[Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-let-expert-stick-his/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zihan Wang, Deli Chen, Damai Dai, et al.*2024 · 17 citations*
- [← back to](https://md.research.elamur.ai/free/en/countries/philippines/) — Philippines