All datasets / tafseer-nayeem
tafseer-nayeem/KidLM-corpus
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@inproceedings{nayeem-rafiei-2024-kidlm,
title = "{K}id{LM}: Advancing Language Models for Children {--} Early Insights and Future Directions",
author = "Nayeem, Mir Tafseer and
Rafiei, Davood",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.277",
pages = "4813--4836",
abstract = "Recent studies highlight the potential of large language models in creating educational tools for children, yet significant challenges remain in maintaining key child-specific properties such as linguistic nuances, cognitive needs, and safety standards. In this paper, we explore foundational steps toward the development of child-specific language models, emphasizing the necessity of high-quality pre-training data. We introduce a novel user-centric data collection pipeline that involves gathering and validating a corpus specifically written for and sometimes by children. Additionally, we propose a new training objective, Stratified Masking, which dynamically adjusts masking probabilities based on our domain-specific child language data, enabling models to prioritize vocabulary and concepts more suitable for children. Experimental evaluations demonstrate
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dataset_licence({ "id": "tafseer-nayeem/KidLM-corpus" })
signal: "restrictive"
stated_licence: "cc-by-nc-sa-4.0"
sources: 0