Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives
Leo Schwinn, Yan Scholten, Tom Wollschläger, Sophie Xhonneux, Stephen Casper, Stephan Günnemann, … (+1 more) — 2025-02-17 — arXiv
Summary
Position paper arguing that adversarial robustness research for LLMs risks repeating mistakes from past adversarial ML research, proposing a cybersecurity-based taxonomy and calling for realigned research objectives focused on measurability, reproducibility, and comparability.
Source
- Link: https://arxiv.org/abs/2502.11910
- Listed in the Shallow Review of Technical AI Safety 2025 under 1 agenda(s):
- various-redteams — Evals