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cs.CL2025
dots.llm1 Technical Report
Bi Huo, Bin Tu, Cheng Qin +24
Mixture of Experts (MoE) models have emerged as a promising paradigm for scaling language models efficiently by activating only a subset of parameters for each input token. In this…
cs.CL2025
Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Luping Wang, Sheng Chen, Linnan Jiang +4
The large models, as predicted by scaling raw forecasts, have made groundbreaking progress in many fields, particularly in natural language generation tasks, where they have approa…