Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Alphapruning: Using heavy-tailed self regularization theory for improved layer-wise pruning of large language models
Recent work on pruning large language models (LLMs) has shown that one can eliminate a
large number of parameters without compromising performance, making pruning a …
large number of parameters without compromising performance, making pruning a …
Model balancing helps low-data training and fine-tuning
Recent advances in foundation models have emphasized the need to align pre-trained
models with specialized domains using small, curated datasets. Studies on these foundation …
models with specialized domains using small, curated datasets. Studies on these foundation …
Rank Also Matters: Hierarchical Configuration for Mixture of Adapter Experts in LLM Fine-Tuning
P Cong, W Liu, W Yu, H Zhao, T Yang - arxiv preprint arxiv:2502.03884, 2025 - arxiv.org
Large language models (LLMs) have demonstrated remarkable success across various
tasks, accompanied by a continuous increase in their parameter size. Parameter-efficient …
tasks, accompanied by a continuous increase in their parameter size. Parameter-efficient …