Correct but Unselectable: The Hidden Interface Tax in Multi-Candidate Reasoning
Read the original on arXiv Machine Learning →The Flow has not summarised this story yet — read it at arXiv Machine Learning.
The Flow has not summarised this story yet — read it at arXiv Machine Learning.
arXiv:2607. 17531v1 Announce Type: cross Abstract: Test-time collaboration, including self-consistency, best-of-N selection, critic models, and verifier pipelines, is often credited with broadly improving LLM reasoning, yet its gains are uneven and sometimes negative.
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ReSolve is a training‑free inference method that reuses candidate reasoning by selectively moderating generative outputs. It examines existing derivations when candidates disagree or lack a parseable answer, then incorporates new solutions into a bounded loop. On 130 competition‑mathematics problems, ReSolve achieves 100 and 99 correct answers with significantly fewer tokens than eight‑sample self‑consistency, while a controlled ablation shows that visible derivations improve accuracy.
The paper introduces OMVV, an online multi-verifier algorithm that maintains a pool of weak verifiers with varying costs and performance. It adaptively selects a verifier each round using an online score combiner and exponential-weights routing, providing distribution-free guarantees on false-accept and false-reject rates. Experiments on reasoning benchmarks show OMVV achieves higher accuracy at lower verification cost than any single fixed verifier across different budgets.
ORSMT is a tool that uses Satisfiability Modulo Theories to verify and repair artifacts produced by large language models when automating optimization modeling from natural language. It provides a typed semantic interface, exact SMT relation queries, and mechanisms to align decisions, project auxiliary variables, and reconstruct artifacts, thereby improving model-code match rates across thousands of problems. The system demonstrates significant gains in correctness and matching rates compared to existing methods such as ReLoop and Opt‑Verifier.