Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation
Paper • 2603.19220 • Published • 69
Post training
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Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR
Paper • 2605.20164 • Published • 2 -
GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment
Paper • 2605.19577 • Published • 53 -
EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL
Paper • 2605.18703 • Published • 44 -
Mid-Training with Self-Generated Data Improves Reinforcement Learning in Language Models
Paper • 2605.08472 • Published • 3 -
Self-Distilled Agentic Reinforcement Learning
Paper • 2605.15155 • Published • 106 -
Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis
Paper • 2605.14392 • Published • 8 -
RewardHarness: Self-Evolving Agentic Post-Training
Paper • 2605.08703 • Published • 9 -
RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards
Paper • 2605.10899 • Published • 74 -
Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents
Paper • 2605.10832 • Published • 21 -
Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction
Paper • 2605.12070 • Published • 16 -
Reward Hacking in Rubric-Based Reinforcement Learning
Paper • 2605.12474 • Published • 5 -
AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration -- Learning from Cheap, Optimizing Expensive
Paper • 2605.11518 • Published • 4 -
DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification
Paper • 2605.09269 • Published • 6 -
DeepRefine: Agent-Compiled Knowledge Refinement via Reinforcement Learning
Paper • 2605.10488 • Published • 3