3 papers
cs.CL2025
Topic Over Source: The Key to Effective Data Mixing for Language Models Pre-training
Jiahui Peng, Xinlin Zhuang, Jiantao Qiu +4
The performance of large language models (LLMs) is significantly affected by the quality and composition of their pre-training data, which is inherently diverse, spanning various l…
cs.CL2025
Meta-rater: A Multi-dimensional Data Selection Method for Pre-training Language Models
Xinlin Zhuang, Jiahui Peng, Ren Ma +7
The composition of pre-training datasets for large language models (LLMs) remains largely undisclosed, hindering transparency and efforts to optimize data quality, a critical drive…
cs.CL2025
Efficient Pretraining Data Selection for Language Models via Multi-Actor Collaboration
Tianyi Bai, Ling Yang, Zhen Hao Wong +9
Efficient data selection is crucial to accelerate the pretraining of language model (LMs). While various methods have been proposed to enhance data efficiency, limited research has…