A survey on stability of learning with limited labelled data and its sensitivity to the effects of randomness
Learning with limited labelled data, such as prompting, in-context learning, fine-tuning, meta-
learning, or few-shot learning, aims to effectively train a model using only a small amount of …
learning, or few-shot learning, aims to effectively train a model using only a small amount of …
Bc4llm: Trusted artificial intelligence when blockchain meets large language models
H Luo, J Luo, AV Vasilakos - ar** society's
production methods and productivity, and also changing the paradigm of scientific research …
production methods and productivity, and also changing the paradigm of scientific research …
When gradient descent meets derivative-free optimization: A match made in black-box scenario
Large pre-trained language models (PLMs) have garnered significant attention for their
versatility and potential for solving a wide spectrum of natural language processing (NLP) …
versatility and potential for solving a wide spectrum of natural language processing (NLP) …