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Sprint projectSep 14, 2026Lübeck, Germany

What Transfers Across Model Generators? Testing Process Representations Across DeepSeek, Claude, and GPT

Kishore Kumar Mariappan · Team TPRN

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: What Transfers Across Model Generators? Testing Process Representations Across DeepSeek, Claude, and GPT

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This project is a companion continuation of "The Missing Process: Reconstructing Distributed Agent Activity from Partial Traces", which develops the Temporal-Persistence Reconstruction Network (TPRN) programme. Here, we test whether process representations learned on one model generator retain signal when another generator realizes the same underlying synthetic process. We use 100 matched process cards independently realized by DeepSeek V3.2, Claude Sonnet 5, and GPT-5.6 Sol, producing 300 synthetic episodes. A compact flow/persistence representation achieves mean cross-generator balanced accuracy of 0.610, while a deterministic strict reference retains non-zero recall in every generator direction under a separate 1%-prevalence synthetic stress test. This is a new-generator, familiar-process test—not unseen-process generalization. A public Collusion Wiki ranking result is withheld after a tie-order audit, leaving real-trace transfer unresolved.

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  1. Relevant question, and experiments, though could have been presented more clearly

Cite this project

@misc{mariappan2026transfers,
  title = {{What Transfers Across Model Generators? Testing Process Representations Across DeepSeek, Claude, and GPT}},
  author = {Kishore Kumar Mariappan},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/what-transfers-across-model-generators-testing-process-representations-across-deepseek-claude-and-gpt-0j7c}},
  url = {https://apartresearch.com/sprints/projects/what-transfers-across-model-generators-testing-process-representations-across-deepseek-claude-and-gpt-0j7c}
}

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