/human-and-machine-confidence-in-truthfulness

repository for the JDIQ paper "Combining Human and Machine Confidence in Truthfulness Assessment"

human-and-machine-confidence-in-truthfulness

repository for the JDIQ paper "Combining Human and Machine Confidence in Truthfulness Assessment"

Overview

  • to be added

Deep Learning Models

The models used in the work are the following:

each model can be used as follows (example provided for the last model):

from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kevinr/Confidence-bert-base-uncased-Loss_MSE-Bin_Nobin")
model = AutoModelForSequenceClassification.from_pretrained("kevinr/Confidence-bert-base-uncased-Loss_MSE-Bin_Nobin")

Data

to be added.