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In "auto-CoT", [46] 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. When prompted with a new question, CoT examples to the ...
The name is a play on words based on the earlier concept of one-shot learning, in which classification can be learned from only one, or a few, examples. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. [1]
The goal of response prompting is to transfer stimulus control from the prompt to the desired discriminative stimulus. [1] Several response prompting procedures are commonly used in special education research: (a) system of least prompts, (b) most to least prompting, (c) progressive and constant time delay, and (d) simultaneous prompting.
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)
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A cot is a camp bed or infant bed. ... Chain-of-thought prompting, a method of engineering language model prompts; In government and military use
The training protocol is based on the principles of applied behavior analysis. [3] The goal of PECS is spontaneous and functional communication. [3] The PECS teaching protocol is based on B. F. Skinner's book, Verbal Behavior, such that functional verbal operants are systematically taught using prompting and reinforcement strategies that will lead to independent communication.
Video modeling (VM) is a mode of teaching that uses video recording and display equipment to provide a visual model of the targeted behaviors or skill. [1] In video self-modeling (VSM), individuals observe themselves performing a behavior successfully on video, and then imitate the targeted behavior.