23 citations · 36 across the 7 of their papers we have counts for
8 papers
Evaluating AI Vocational Skills Through Professional Testing
David Noever, Matt Ciolino
Using a novel professional certification survey, the study focuses on assessing the vocational skills of two highly cited AI models, GPT-3 and Turbo-GPT3.5. The approach emphasizes…
Professional Certification Benchmark Dataset: The First 500 Jobs For Large Language Models
David Noever, Matt Ciolino
The research creates a professional certification survey to test large language models and evaluate their employable skills. It compares the performance of two AI models, GPT-3 and…
Soft Labels for Rapid Satellite Object Detection
Matthew Ciolino, Grant Rosario, David Noever
Soft labels in image classification are vector representations of an image's true classification. In this paper, we investigate soft labels in the context of satellite object detec…
The Turing Deception
David Noever, Matt Ciolino
This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling t…
Soft-labeling Strategies for Rapid Sub-Typing
Grant Rosario, David Noever, Matt Ciolino
The challenge of labeling large example datasets for computer vision continues to limit the availability and scope of image repositories. This research provides a new method for au…
Back Translation Survey for Improving Text Augmentation
Matthew Ciolino, David Noever, Josh Kalin
Natural Language Processing (NLP) relies heavily on training data. Transformers, as they have gotten bigger, have required massive amounts of training data. To satisfy this require…
Local Translation Services for Neglected Languages
David Noever, Josh Kalin, Matt Ciolino +2
Taking advantage of computationally lightweight, but high-quality translators prompt consideration of new applications that address neglected languages. Locally run translators for…
The Chess Transformer: Mastering Play using Generative Language Models
David Noever, Matt Ciolino, Josh Kalin
This work demonstrates that natural language transformers can support more generic strategic modeling, particularly for text-archived games. In addition to learning natural languag…