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cs.LG2025
Mitigating Catastrophic Forgetting in Large Language Models with Forgetting-aware Pruning
Wei Huang, Anda Cheng, Yinggui Wang
Recent advancements in large language models (LLMs) have shown impressive capabilities in various downstream tasks but typically face Catastrophic Forgetting (CF) during fine-tunin…
cs.CL2025
DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression
Wei Huang, Huang Wei, Yinggui Wang
Large language models (LLMs) excel in general tasks but struggle with domain-specific ones, requiring fine-tuning with specific data. With many open-source LLMs available, selectin…
cs.LG2025
DPF-CM: A Data Processing Framework with Privacy-Preserving Vector Databases for Chinese Medical LLMs Training and Deployment
Wei Huang, Anda Cheng, Zhao Zhang +1
Current open-source training pipelines for Chinese medical language models predominantly emphasize optimizing training methodologies to enhance the performance of large language mo…