3 papers
cs.CL2025
Exploring Polyglot Harmony: On Multilingual Data Allocation for Large Language Models Pretraining
Ping Guo, Yubing Ren, Binbin Liu +6
Large language models (LLMs) have become integral to a wide range of applications worldwide, driving an unprecedented global demand for effective multilingual capabilities. Central…
cs.LG2025
TiKMiX: Take Data Influence into Dynamic Mixture for Language Model Pre-training
Yifan Wang, Binbin Liu, Fengze Liu +6
The data mixture used in the pre-training of a language model is a cornerstone of its final performance. However, a static mixing strategy is suboptimal, as the model's learning pr…
cs.CL2025
QuaDMix: Quality-Diversity Balanced Data Selection for Efficient LLM Pretraining
Fengze Liu, Weidong Zhou, Binbin Liu +8
Quality and diversity are two critical metrics for the training data of large language models (LLMs), positively impacting performance. Existing studies often optimize these metric…