view article Article One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMO nvidia • 1 day ago • 12
ProgramDistill: From Interactive Web Apps to Verifiable Reference-Guided SWE Tasks Paper • 2609.18805 • Published 23 days ago • 67
Weak-to-Strong Generalization via Direct On-Policy Distillation Paper • 2607.05394 • Published Jul 8 • 144
SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring Paper • 2608.09802 • Published Aug 10 • 85
LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget Paper • 2607.14952 • Published Jul 16 • 93
Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why Paper • 2605.10889 • Published May 11 • 6
SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization Paper • 2604.02268 • Published Apr 2 • 100
Nemotron-Post-Training-v3 Collection Collection of datasets used in the post-training phase of Nemotron Nano, Super, and Ultra v3. • 50 items • Updated Aug 11 • 204
Nemotron-Post-Training-v3 Collection Collection of datasets used in the post-training phase of Nemotron Nano, Super, and Ultra v3. • 50 items • Updated Aug 11 • 204
BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing? Paper • 2603.03194 • Published Mar 3 • 57