Character as a Latent Variable in Large Language Models: A Mechanistic Account of Emergent Misalignment and Conditional Safety Failures
Character as a Latent Variable in Large Language Models: A Mechanistic Account of Emergent Misalignment and Conditional Safety Failures explores Exploring character formation in LLMs as a key factor in emergent misalignment and safety risks.. Commercial viability score: 2/10 in AI Safety and Alignment.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Higher Viability"Dark Triad" Model Organisms of Misalignment: Narrow Fine-Tuning Mirrors Human Antisocial BehaviorViability: 7.0
- Higher ViabilityMechanistic Origin of Moral Indifference in Language ModelsViability: 5.0
- Higher ViabilityNarrow fine-tuning erodes safety alignment in vision-language agentsViability: 5.0
- Higher ViabilityAlignment Backfire: Language-Dependent Reversal of Safety Interventions Across 16 Languages in LLM Multi-Agent SystemsViability: 4.0
- Higher ViabilityThe Fragility Of Moral Judgment In Large Language Models