Rapid switching and multi-adapter fusion via sparse high rank adapters

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
[Free GPT-4]
[DeepSeek]
[PDF] arxiv.org

SFT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity

X Yang, J Leng, G Guo, J Zhao, R Nakada… - arxiv preprint arxiv …, 2024 - arxiv.org
Current PEFT methods for LLMs can achieve either high quality, efficient training, or
scalable serving, but not all three simultaneously. To address this limitation, we investigate …
Tallenna Viittaa Viittausten määrä 1 Aiheeseen liittyviä artikkeleita Kaikki 4 versiota HTML-versio
[Free GPT-4]
[DeepSeek]
[PDF] arxiv.org

Is Parameter Collision Hindering Continual Learning in LLMs?

S Yang, KP Ning, YY Liu, JY Yao, YH Tian… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) often suffer from catastrophic forgetting when learning
multiple tasks sequentially, making continual learning (CL) essential for their dynamic …
Tallenna Viittaa Aiheeseen liittyviä artikkeleita Kaikki 3 versiota HTML-versio