Search results
Results from the WOW.Com Content Network
The term zero-shot learning itself first appeared in the literature in a 2009 paper from Palatucci, Hinton, Pomerleau, and Mitchell at NIPS’09. [5] This terminology was repeated later in another computer vision paper [6] and the term zero-shot learning caught on, as a take-off on one-shot learning that was introduced in computer vision years ...
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 ...
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)
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.
One-shot learning is an object categorization problem, found mostly in computer vision.Whereas most machine learning-based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.
Model size License Comments Stanford bunny: 1993-94 [11] Greg Turk, Marc Levoy at Stanford University: Ceramic rabbit [12] 69,451 triangles [11] Figurine of unknown authorship and licensing status, scan itself released under a two-clause BSD license. A test of range scanning physical objects. Originally .ply file. Stanford dragon: 1996 [11 ...
Field test – Modeler performs data gathering of subject under test Post-test modeling – Subject under test model input parameters are matched with subject under test–field–test output values Model validation/accreditation – Modeler provides sufficient evidence to a tester that a simulation adequately replicates field testing
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 ...