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CoT examples can be generated by LLM themselves. In "auto-CoT", [60] a library of questions are converted to vectors by a model such as BERT. The question vectors are clustered. Questions nearest to the centroids of each cluster are selected. An LLM does zero-shot CoT on each question. The resulting CoT examples are added to the dataset.
Few-shot learning and one-shot learning may refer to: Few-shot learning, a form of prompt engineering in generative AI; One-shot learning (computer vision)
Prompt injection is a family of related computer security exploits carried out by getting a machine learning model which was trained to follow human-given instructions (such as an LLM) to follow instructions provided by a malicious user. This stands in contrast to the intended operation of instruction-following systems, wherein the ML model is ...
A question answering task is considered "open book" if the model's prompt includes text from which the expected answer can be derived (for example, the previous question could be adjoined with some text which includes the sentence "The Sharks have advanced to the Stanley Cup finals once, losing to the Pittsburgh Penguins in 2016." [122]).
The Alexander brothers were charged with conspiring to "repeatedly and violently drug, sexually assault, and rape dozens of victims."
Montrell Johnson Jr.'s 5-yard touchdown run with 7:40 remaining in the fourth quarter gave Florida a 24-17 win over No. 9 Ole Miss on Saturday in Gainesville. Ole Miss had a chance to tie the game ...
However it comes at a cost: due to encoder-only architecture lacking a decoder, BERT can't be prompted and can't generate text, while bidirectional models in general do not work effectively without the right side, thus being difficult to prompt. As an illustrative example, if one wishes to use BERT to continue a sentence fragment "Today, I went ...
Match Made in Hell: How the 'Lonely Hearts' Killers Seduced Their Prey with Newspaper Ads During Murderous Spree