3 citations · 6 across the 5 of their papers we have counts for
10 papers
Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models
Philip Feldman, Aaron Dant, James R. Foulds +1
Text analysis of social media for sentiment, topic analysis, and other analysis depends initially on the selection of keywords and phrases that will be used to create the research…
Ethics, Rules of Engagement, and AI: Neural Narrative Mapping Using Large Transformer Language Models
Philip Feldman, Aaron Dant, David Rosenbluth
The problem of determining if a military unit has correctly understood an order and is properly executing on it is one that has bedeviled military planners throughout history. The…
Analyzing COVID-19 Tweets with Transformer-based Language Models
Philip Feldman, Sim Tiwari, Charissa S. L. Cheah +2
This paper describes a method for using Transformer-based Language Models (TLMs) to understand public opinion from social media posts. In this approach, we train a set of GPT model…
Navigating Human Language Models with Synthetic Agents
Philip Feldman, Antonio Bucchiarone
Modern natural language models such as the GPT-2/GPT-3 contain tremendous amounts of information about human belief in a consistently testable form. If these models could be shown…
Training robust anomaly detection using ML-Enhanced simulations
Philip Feldman
This paper describes the use of neural networks to enhance simulations for subsequent training of anomaly-detection systems. Simulations can provide edge conditions for anomaly det…
Belief places and spaces: Mapping cognitive environments
Philip Feldman, Aaron Dant, Wayne Lutters
Beliefs are not facts, but they are factive - they feel like facts. This property is what can make misinformation dangerous. Being able to deliberately navigate through a landscape…