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Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences

Sweta Karlekar, Carolina Zheng, Magnus Saebo, Nicolas Beltran-Velez, Shuyang Yu, John Bowlan ยท Feb 25, 2026

Citations: 0
Pairwise Preference Automatic Metrics Math
  • Building on this observation, we introduce Duel-Evolve, an evolutionary optimization algorithm that replaces external scalar rewards with pairwise preferences elicited from the same LLM used to generate candidates.
  • Results show that pairwise self-preferences provide strong optimization signal for test-time improvement over large, discrete output spaces.

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