Are you looking for better training data for your models? Let me tell you about dynamic adversarial data collection!
I had a large enterprise customer asking me to incorporate this workflow into a Hugging Face private hub demo. Here are some resources I found useful: Chris Emezue put together a blog post: “How to train your model dynamically using adversarial data” and a real-life example using MNIST using Spaces.
If you want an academic paper that details this process, check out: Analyzing Dynamic Adversarial Training Data in the Limit. By using this approach, this paper found models made 26% fewer errors on the expert-curated test set.
And if you prefer a video — check out my Tik Tok:
https://www.tiktok.com/@rajistics/video/7123667796453592366?is_from_webapp=1&sender_device=pc&web_id=7106277315414181422