gpt-2-output-dataset VS oxen-release

especially: "Our classifier is not fully reliable. In our evaluations on a “challenge set” of English texts, our classifier correctly identifies 26% of AI-written text (true positives) as “likely AI-written,” while incorrectly labeling human-written text as AI-written 9% of the time (false positives). Our classifier’s reliability typically improves as the length of the input text increases. Compared to our previously released classifier, this new classifier is significantly more reliable on text from more recent AI systems." Many other classifiers are similar, e.g.:

Links search found: https://github.com/openai/gpt-2-output-dataset (dataset? I want GPT, Pre-trained model).

Source: the literal source code and paper by the original creators of a detector that most of these knockoff detectors are based on.

OpenAI published a detector themselves that seems to be quite good. https://github.com/openai/gpt-2-output-dataset/tree/master/detector

Here is OpenAI's own detector, but it's not impossible to beat by just doing some fairly basic stuff with things like automatic paraphrasing.

To a certain extent, GPT-2 worked because of the smaller dataset of just 40GB. Even in that model, researchers running detection found accurate results only in the:

We've been working on a data version control system called "oxen" optimized for large unstructured datasets that we are seeing more and more with the advent of many of the generative AI techniques.

Many of these datasets have many many images, videos, audio files, text as well as structured tabular datasets that git or git-lfs just falls flat on.

Would love anyone to kick the tires on it and let us know what you think:

https://github.com/Oxen-AI/oxen-release

The commands are mirrored after git so it is easy to learn, but optimized under the hood for larger datasets.

Super cool! Would love to see an integration with Oxen and their data version control https://github.com/Oxen-AI/oxen-release

We have been working on a data version control tool called Oxen that is tackling many of your needs. Feel free to check it out here:

https://github.com/Oxen-AI/oxen-release#-oxen

Going down your list of requirements, Oxen has:

* Data versioning, similar paradigm to git, but built from the ground up for large ML datasets

We've been working on some open source tooling called "oxen" that was built for large datasets of images, video, audio, text etc. We wanted to solve the exact problem you're flagging here with git.

Feel free to check it out here https://github.com/Oxen-AI/oxen-release#-oxen would love any feedback!