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Author

V. Srinivasan

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#artificial intelligence Preprint Oct 2026

Priming Base Models for Agentic Post-Training: An Open Midtraining Recipe

Frontier models, general-purpose and domain-specific alike, now include a midtraining stage between pretraining and post-training, but little has been published about how this stage is built. We present an open midtraining recipe that primes base models for agentic post-training, and we show its effectiveness on two Ne...

Soumye Singhal, Joseph Jennings, Ka-Shun Shum et al. · 0 citations
#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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