Target-ESS Tempered Policy Optimization (TETPO): Smooth Variance Control via Bridge Importance Sampling
cs.LG, cs.AI
Submitted: 2026-10-10
Updated: 2026-10-10
Sources
- Smaller Models, Better Rejects: Preference Distillation Scaling
- AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning
- Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
- PipelineRL: Faster On-policy Reinforcement Learning for Long Sequence Generation
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training
- Group Sequence Policy Optimization
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