Author

N. Maloyan

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Preprint Oct 2026

Evaluating and Improving the Robustness of Large Language Models to Input Sequence Variations

A generative robustness metric based on the Jensen-Shannon divergence between per-step output distributions under small input perturbations is proposed, R_stab(f), which attests tool calls with HMAC-protected packets at under 0.1 ms per call, and the Commit Boundary isolation pattern.

N. Maloyan · 0 citations

#machine learning Preprint Oct 2026

Evaluating and Improving the Robustness of Large Language Models to Input Sequence Variations

Large language models (LLMs) in production systems face prompt injections, trojans (backdoors), and manipulation of automatic quality metrics. This thesis develops models, methods, and algorithms for evaluating and improving LLM robustness to adversarial input sequence variations. We propose R_stab(f), a generative rob...

N. Maloyan · 0 citations