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PoTRE: Test-Time Reasoning inspired by Cognitive Heterogeneity

Research LLM Agents

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Merged summary

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.

Sources (1)

PoTRE: Test-Time Reasoning inspired by Cognitive Heterogeneity

arXiv cs.AI Anmol Kankariya, Sercan Ö. Arık 2026-07-22 arXiv:2607.20268
Public signals Semantic Scholar citations 0 · Semantic Scholar influential citations 0
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 0 · Influential citations 0 X · N/A Fetched 2026-08-06 16:13:09.442915 UTC

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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