Identity as Attractor: Geometric Evidence for Persistent Agent Architecture in LLM Activation Space

1. 1Run experiments on LLMs like Llama 3.1 to analyze hidden states and attractor behavior
2. 2Compare original cognitive_core with paraphrased versions to identify persistent patterns
3. 3Apply geometric analysis to visualize and quantify attractor-like dynamics in activation space
4. 4Configure and test different LLM architectures to validate findings
5. 5Analyze results to inform design of more efficient and effective persistent agent architectures

NLP researchers and AI engineers can benefit from understanding the attractor-like dynamics of large language models to improve agent architecture and cognitive core design

💡 Identity acts as an attractor in LLM activation space, exhibiting persistent patterns across paraphrased cognitive cores

🤖 Identity as attractor: geometric evidence for persistent agent architecture in LLM activation space! #LLMs #AI #NLP