Uniform Race: Parameter-Free Approximate Rejection Sampling

arXiv:2609.34639 · cs.LG, stat.ML · Submitted 2026-09-28 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Accuracy — 54× in this paper · explained in 1 episode
• Calibration — 14× in this paper · explained in 7 episodes
• Sample Complexity — 6× in this paper · explained in 15 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Fidelity — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Test-time Scaling — 2× in this paper · explained in 2 episodes
• Verifier — 2× in this paper · explained in 2 episodes
• Best-of-N Sampling — 1× in this paper · explained in 2 episodes
• COMPARISON WITH SAMPLING IMPORTANCE RESAMPLING — 1× in this paper
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Institute of Electrical and Electronics Engineers — 1× in this paper
• Intrinsic Dimension — 1× in this paper · explained in 2 episodes
• Minimax optimality — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Regret — 1× in this paper · explained in 3 episodes

Sources

• Training Verifiers to Solve Math Word Problems
• On importance sampling and independent Metropolis-Hastings with an unbounded weight function
• The Llama 3 Herd of Models
• Measuring Mathematical Problem Solving With the MATH Dataset
• Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking
• Exact Convergence Rate Analysis of the Independent Metropolis-Hastings Algorithms

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