AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
2 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This work proposes a family of counterfactual test-time augmentation (CTTA) methods, and proves that the optimal shortcut-invariant predictor is a member of this CTTA family, and describes its weights.
The method is model-agnostic and can be applied at inference time without modifying model parameters, providing a flexible mechanism for reducing hidden influences and improving the reliability and safety of LLM-assisted decision making.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.