Lester James V. Miranda
Orcid: 0000-0002-7872-6464
According to our database1,
Lester James V. Miranda authored at least 26 papers
between 2018 and 2026.
Collaborative distances:
Collaborative distances:
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Bibliography
2026
CoRR, April, 2026
Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation.
CoRR, April, 2026
2025
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia.
CoRR, March, 2025
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
The UD-NewsCrawl Treebank: Reflections and Challenges from a Large-scale Tagalog Syntactic Annotation Project.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
2024
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages.
CoRR, 2024
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
2023
2022
2019
2018
J. Open Source Softw., 2018
Feature Extraction Using a Mutually-Competitive Autoencoder for Protein Function Prediction.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018
A Deep Learning Approach Based on Stacked Denoising Autoencoders for Protein Function Prediction.
Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference, 2018