Identity as Attractor: Geometric Evidence for Persistent Agent Architecture in LLM Activation Space
📰 ArXiv cs.AI
Discover how identity acts as an attractor in LLM activation space, revealing persistent agent architecture through geometric analysis
Action Steps
- Run experiments on LLMs like Llama 3.1 to analyze hidden states and attractor behavior
- Compare original cognitive_core with paraphrased versions to identify persistent patterns
- Apply geometric analysis to visualize and quantify attractor-like dynamics in activation space
- Configure and test different LLM architectures to validate findings
- Analyze results to inform design of more efficient and effective persistent agent architectures
Who Needs to Know This
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
Key Insight
💡 Identity acts as an attractor in LLM activation space, exhibiting persistent patterns across paraphrased cognitive cores
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🤖 Identity as attractor: geometric evidence for persistent agent architecture in LLM activation space! #LLMs #AI #NLP
Key Takeaways
Discover how identity acts as an attractor in LLM activation space, revealing persistent agent architecture through geometric analysis
Full Article
Title: Identity as Attractor: Geometric Evidence for Persistent Agent Architecture in LLM Activation Space
Abstract:
arXiv:2604.12016v1 Announce Type: new Abstract: Large language models map semantically related prompts to similar internal representations -- a phenomenon interpretable as attractor-like dynamics. We ask whether the identity document of a persistent cognitive agent (its cognitive_core) exhibits analogous attractor-like behavior. We present a controlled experiment on Llama 3.1 8B Instruct, comparing hidden states of an original cognitive_core (Condition A), seven paraphrases (Condition B), and se
Abstract:
arXiv:2604.12016v1 Announce Type: new Abstract: Large language models map semantically related prompts to similar internal representations -- a phenomenon interpretable as attractor-like dynamics. We ask whether the identity document of a persistent cognitive agent (its cognitive_core) exhibits analogous attractor-like behavior. We present a controlled experiment on Llama 3.1 8B Instruct, comparing hidden states of an original cognitive_core (Condition A), seven paraphrases (Condition B), and se
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