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cs.DC2026
TAOT: Topology-Aware Optimal Transport for Dynamic Expert Replica Placement in MoE Training
Lingyun Zhang, Henghua Zhang, Shilei Gu +5
Mixture-of-Experts (MoE) has become a key architecture for scaling large language models (LLMs), yet its dynamic routing causes severe load imbalance in expert-parallel training. E…
cs.CL2026
CVPO: Enhancing LLM Reinforcement Learning Reasoning via Value-Variance Adaptation and Dynamic Curriculum Learning
Ziqi Jia, Yalu Ouyang, Bo Pang +5
Reinforcement learning (RL) has emerged as an effective method for enhancing the reasoning capabilities of large language models (LLMs). However, existing methods suffer from insuf…
cs.LG2026
Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction
Ziyao Tang, Pengkun Jiao, Xinhang Chen +3
Given the quadratic complexity of attention, KV cache eviction is vital to accelerate model inference. Current KV cache eviction methods typically rely on instantaneous heuristic m…