Adversarial Training
adversarial-trainingapproachPath: /knowledge-base/responses/adversarial-training/
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"summary": "Adversarial training, universally adopted at frontier labs with \\$10-150M/year investment, improves robustness to known attacks but creates an arms race dynamic and provides no protection against model deception or novel attack categories. While necessary for operational security, it only defends external attacks rather than addressing fundamental alignment challenges.",
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"text": "GCG attack",
"url": "https://arxiv.org/abs/2307.15043",
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"resourceTitle": "[2307.15043] Universal and Transferable Adversarial Attacks on Aligned Language Models"
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}Backlinks (12)
| id | title | type | relationship |
|---|---|---|---|
| circuit-breakers | Circuit Breakers / Inference Interventions | approach | — |
| accident-risks | AI Accident Risk Cruxes | crux | — |
| is-ai-xrisk-real | Is AI Existential Risk Real? | crux | — |
| why-alignment-hard | Why Alignment Might Be Hard | argument | — |
| intervention-effectiveness-matrix | Intervention Effectiveness Matrix | analysis | — |
| far-ai | FAR AI | organization | — |
| redwood-research | Redwood Research | organization | — |
| safety-orgs-overview | AI Safety Organizations (Overview) | concept | — |
| paul-christiano | Paul Christiano | person | — |
| alignment-training-overview | Training Methods (Overview) | concept | — |
| deepfakes | Deepfakes | risk | — |
| sleeper-agents | Sleeper Agents: Training Deceptive LLMs | risk | — |