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Jonathan Cohen

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#artificial intelligence Preprint Oct 2026

Before They Can Solve: Predicting Post-Training Coding-Agent Performance from Base Models

How can we predict which base checkpoint is worth an expensive round of agentic post-training? End-to-end pass@$K$ tests whether successful behavior already appears in a base model's distribution, but it is a poor fit for agentic coding: many base checkpoints cannot reliably produce the well-formed tool invocation requ...

Tan Yu, A. Bukharin, Khushi Bhardwaj et al. · 1 citation

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