7 citations · 12 across the 19 of their papers we have counts for
5 papers · 1 filter
Post-Training Language Models for Gold-Medal Performance in Coding Competitions
Aleksander Ficek, Sean Narenthiran, Mehrzad Samadi +2
Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its most challenging settings. We…
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aakshita Chandiramani +544
We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…
Learning Generative Selection for Best-of-N
Shubham Toshniwal, Aleksander Ficek, Siddhartha Jain +5
Scaling test-time compute via parallel sampling can substantially improve LLM reasoning, but is often limited by Best-of-N selection quality. Generative selection methods, such as…
Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models
Mehrzad Samadi, Aleksander Ficek, Sean Narenthiran +5
Competitive programming has become a rigorous benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). The International Olympiad in…
GenSelect: A Generative Approach to Best-of-N
Shubham Toshniwal, Ivan Sorokin, Aleksander Ficek +2
Generative reward models with parallel sampling have enabled effective test-time scaling for reasoning tasks. Current approaches employ pointwise scoring of individual solutions or…