- BiasLLMs may generate problematic outputs that negatively impact the model’s performance on downstream tasks and exhibit biases that could deteriorate model performance. Some of these can be mitigated through effective prompting strategies, but more advanced solutions like regularization and filtering may be required.
- Distribution of ExamplesDoes the distribution of examples affect model performance or introduce biases in some way during few-shot learning? We can conduct a simple test here.
- Prompt 分享
将这段话翻译成法语。
再提供一些英文文本供你翻译。
你还能翻译哪些语言？
深度思考