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

Reported by arXiv cs.CR (Narek Maloyan)

Summary by Cyber Security News5 Oct 2026, 06:00 CEST

About this summary. This is a short, independently written summary of an article first published by arXiv cs.CR. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.02432

arXiv:2610.02432v1 Announce Type: new Abstract: 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.

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