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PoTRE: Test-Time Reasoning inspired by Cognitive Heterogeneity

arXiv cs.AI LLM Agents Anmol Kankariya, Sercan Ö. Arık 2026-07-22

TL;DR - PoTRE is a test-time reasoning framework that combines four specialized agents through adaptive aggregation. It reports stronger complex-reasoning performance with similar or fewer inference tokens than heavily scaled homogeneous baselines.

  • Uses adversarial refinement, hierarchical planning, spectrum search, and direct chain reasoning agents.
  • Aggregates outputs through candidate selection, semantic synthesis, or neuro-symbolic verification.
  • Evaluated on ARC-AGI-2, Humanity’s Last Exam, and PRBench Finance.
  • Achieves 49.92% accuracy on HLE, reported as a new state-of-the-art official score.

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