Adversarially Trained Linear Transformers Are Optimal Robust In-Context Learners for Gaussian Mixtures

arXiv:2610.07754 · cs.LG, cs.CV, stat.ML · Submitted 2026-10-06 · Read on arXiv

cs.LG, cs.CV, stat.ML

Submitted: 2026-10-06

Updated: 2026-10-06

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 1× in this paper · explained in 2 episodes

Sources

• How Well Can Transformers Emulate In-context Newton's Method?
• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

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