Alibaba Proposes ERPO: Environmental Regularization for Stable LLM RLHF
alibabagroup · hf · 2026-08-25
Alibaba Group published the paper 'Beyond the Stability-Exploration Dilemma', introducing ERPO (Environmental Regularization for Policy Optimization). ERPO replaces action-side policy regularization with input-side query distribution control to stabilize reinforcement learning for language models while preserving response exploration, addressing the trade-off between stability and exploration.
More from Research
- Statistical Rethinking 2026: 20 Lectures on Causal Inference & Scientific Modeling — RichmanRonald · 2026-08-25
- Simulation-Based Inference: Neural Nets Solve Probability Black Boxes — burkov · 2026-08-25
- WIEN-INR: Neural Representation for Lossless Scientific Data Compression — bravo_abad · 2026-08-25
- NeurIPS 2026 workshop calls for papers on AI failure modes in biology — anshulkundaje · 2026-08-25
- SimCLR & MoCo vs. incremental science — 3scorciav · 2026-08-25
- How to map a new field's 5-year trends without losing your mind — LumilitawNaMangga · 2026-08-25