Author

Markus Kliegl

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Review Oct 2026

Scaling Synthetic Pre-training Data and Evaluation for Indic LLMs

Building capable language models for India requires scalable multilingual data and robust evaluation. We introduce Nemotron-Pretraining-Indic-v1, a synthetic pretraining corpus of approximately 2.83 trillion tokens covering all 22 scheduled Indian languages in native script and twelve in romanized form. It is the large...

Abhinav Khattar, Aishwarya Chhabra, A. Velingker et al. · 0 citations

#artificial intelligence Preprint Oct 2026

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

An open midtraining recipe is presented that primes base models for agentic post-training, and its effectiveness on two Nemotron models of different sizes is shown, improving robustness across agent harnesses on both models.

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