router-aware approach to optimize importance sampling weights

Newer alternatives

Recent methods in the same sub-problem, not yet superseded in the knowledge base.

• PADDPADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning
  Jun 9, 2026
• MESAMESA: Improving MoE Safety Alignment via Decentralized Expertise
  May 30, 2026
• PR2PR2: Predictive Routing Replay for MoE-Based LLM Reinforcement Learning
  May 29, 2026
• RouteHijackRouteHijack: Routing-Aware Attack on Mixture-of-Experts LLMs
  May 1, 2026
• MASCingMASCing: Configurable Mixture-of-Experts Behavior via Activation Steering Masks
  Apr 30, 2026
• F-SOURSparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
  Feb 9, 2026
• SocialNav-MoESocialNav-MoE: A Mixture-of-Experts Vision Language Model for Socially Compliant Navigation with Reinforcement Fine-Tuning
  Dec 15, 2025
• OrdMoEOrdMoE: Preference Alignment via Hierarchical Expert Group Ranking in Multimodal Mixture-of-Experts LLMs
  Nov 24, 2025
• router-aware approach to optimize importance sampling weightsTowards Stable and Effective Reinforcement Learning for Mixture-of-Experts
  Oct 27, 2025
• Mix- and MoE-DPOMix- and MoE-DPO: A Variational Inference Approach to Direct Preference Optimization
  Oct 9, 2025