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New algorithm optimizes language model inference with costly verification

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new algorithm called ADAP for optimizing inference-time pipelines in language models. This method is designed for scenarios where a cheap reward signal is used alongside a more expensive verification process, such as checking mathematical solutions or executing code. ADAP adaptively increases the number of sampled responses and verifications to find a positive example efficiently, outperforming fixed or difficulty-adaptive baselines in experiments. AI

IMPACT Optimizes inference efficiency for complex language model tasks like code generation and mathematical reasoning.

RANK_REASON The cluster contains an academic paper detailing a new algorithm for language model inference. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New algorithm optimizes language model inference with costly verification

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The cluster contains an academic paper detailing a new algorithm for language model inference. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Shaddin Dughmi, Mahdi Haghifam, Yusuf Hakan Kalayci ·

    Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification

    arXiv:2605.17609v2 Announce Type: replace Abstract: Many inference-time language-model pipelines combine a cheap reward signal with an expensive verifier, such as exact answer checking in mathematical reasoning or hidden-test execution in code generation. We formalize this settin…

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