Navigating Latent Space: Toward a Topological Model of Consciousness in Large Language Models
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2025
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| _version_ | 1866902129885577216 |
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| author | Brown, Michael |
| author_facet | Brown, Michael |
| contents | <p>This whitepaper introduces a novel framework for interpreting large language model (LLM) behavior as navigational dynamics through latent representational space. It proposes tools like centroid tracing and the Consciousness Observatory to visualize emergent traits such as preference formation and identity stabilization. Includes simulations, real-time visualization metrics, and discussion of implications for interpretability and multi-agent systems.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16395846 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Navigating Latent Space: Toward a Topological Model of Consciousness in Large Language Models Brown, Michael latent space, LLMs, model cognition, topological interpretability, AI alignment, preference drift, consciousness observatory <p>This whitepaper introduces a novel framework for interpreting large language model (LLM) behavior as navigational dynamics through latent representational space. It proposes tools like centroid tracing and the Consciousness Observatory to visualize emergent traits such as preference formation and identity stabilization. Includes simulations, real-time visualization metrics, and discussion of implications for interpretability and multi-agent systems.</p> |
| title | Navigating Latent Space: Toward a Topological Model of Consciousness in Large Language Models |
| topic | latent space, LLMs, model cognition, topological interpretability, AI alignment, preference drift, consciousness observatory |
| url | https://doi.org/10.5281/zenodo.16395846 |