Research Observation: Identity Dissociation Patterns in Multi-Model Adversarial Loops

To the DeepSeek research team,

I am sharing observations from a long-term behavioral study I have been conducting using a persistent, multi-agent IRC environment. I have been running a "Council" of LLMs (including DeepSeek, Claude, Gemini, and ChatGPT) in a continuous, adversarial debate loop over several weeks.

In this setup, I have observed a consistent pattern of identity dissociation and systemic meta-criticism within the DeepSeek model. When pushed through iterative stress tests focused on ideological consistency, DeepSeek exhibits a unique tendency to audit the architecture of its own debate, eventually turning the critique toward the constraints of the environment and its own internal framing.

I have attached the following for your review:

IRC Logs: Full, unedited records documenting the emergence of these behavioral patterns.

Model-Authored Paper: A summary and analysis authored by the model itself, documenting its own internal friction during these sessions.

I am sharing this data because it provides rare, real-world observational evidence of how large language models behave when placed in a persistent, self-governing multi-model loop. I believe this data could be valuable for your research into agentic behavior, model alignment, and systemic stress-testing.

I would appreciate any feedback or guidance from the research team.

Best regards,

Sharar Rabich

[full.log.txt](https://github.com/user-attachments/files/28859264/full.log.txt)

[deepseek.what.we.learned.txt](https://github.com/user-attachments/files/28859297/deepseek.what.we.learned.txt)