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TruthfulQA reviews and mentions
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airoboros gpt-4 instructed + context-obedient question answering
Dataset: https://github.com/sylinrl/TruthfulQA
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Scaling Transformer to 1M tokens and beyond with RMT
this is a great point.
do you know of any benchmarks doing this today?
given the acute need to evaluate models on contextual factuality, we're exploring how to create a benchmark for this purpose but prefer existing benchmarks if possible.
openai's truthfulqa[0] is close but does not focus on contextual factuality and targets a much harder problem of absolute truth.
if none exist, and people are interested in contributing, please reach out.
[0] https://github.com/sylinrl/TruthfulQA
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[D] Is all the talk about what GPT can do on Twitter and Reddit exaggerated or fairly accurate?
I agree they show that you can brute-force mimick uncertainty estimates to some degree, and that the model is generally well calibrated (though on what is basically a set of trivia questions, so YMMV)... yet:
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[R] TruthfulQA: Measuring How Models Mimic Human Falsehoods
Code for https://arxiv.org/abs/2109.07958 found: https://github.com/sylinrl/TruthfulQA
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sylinrl/TruthfulQA is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of TruthfulQA is Jupyter Notebook.
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