2 papers
cs.CL2025
Balancing Speciality and Versatility: A Coarse to Fine Framework for Mitigating Catastrophic Forgetting in Large Language Models
Hengyuan Zhang, Yanru Wu, Dawei Li +4
Aligned Large Language Models (LLMs) showcase remarkable versatility, capable of handling diverse real-world tasks. Meanwhile, aligned LLMs are also expected to exhibit speciality,…
cs.CL2024
CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models
Jiawei Gu, Zacc Yang, Chuanghao Ding +2
Large Language Models (LLMs) excel in diverse tasks but often underperform in specialized fields due to limited domain-specific or proprietary corpus. Continual pre-training (CPT)…