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Questions and Answers
What is the main obstacle to the widespread application of large-scale models in various scenarios?
What is the main obstacle to the widespread application of large-scale models in various scenarios?
- Significant computational resources and training time (correct)
- Limited set of global parameters
- Inability to combine different computational modules
- Random routing phenomenon
What is a prominent paradigm in recent research to address the issue of demanding computational resources for fine-tuning large language models?
What is a prominent paradigm in recent research to address the issue of demanding computational resources for fine-tuning large language models?
- Parameter-Efficient Fine-Tuning (PEFT) (correct)
- LoRA
- Mixture of Experts (MoE)
- Contrastive learning
Which method was introduced in the text to address the random routing phenomenon observed in Mixture of Experts (MoE)?
Which method was introduced in the text to address the random routing phenomenon observed in Mixture of Experts (MoE)?
- LoRA
- MoELoRA
- PEFT
- Contrastive learning (correct)
How did MoELoRA perform compared to LoRA in math reasoning tasks?
How did MoELoRA perform compared to LoRA in math reasoning tasks?
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Which approach outperformed LoRA significantly with the same number of parameters in the experiments conducted on math and common-sense reasoning benchmarks?
Which approach outperformed LoRA significantly with the same number of parameters in the experiments conducted on math and common-sense reasoning benchmarks?
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