Fighting LLM Hallucinations
A technique to enhance truthfulness without retraining
Adaptive Activation Steering improves LLM truthfulness by manipulating internal model activations to reduce hallucinations.
- Creates a truthfulness direction in model activation space that can be applied at inference time
- Works across diverse hallucination categories including fact-based, commonsense, and mathematical reasoning
- Requires no model retraining or fine-tuning, making implementation practical and efficient
- Achieves significant reduction in hallucinations while maintaining response quality
This research is critical for security applications where false AI-generated information could lead to misinformation campaigns, compromised decision-making, or exploitation of AI vulnerabilities.