2 papers
cs.AR2026
MonoMoE: An Efficient Fused Mega-kernel for Quantized MoE Decoding
Yu Gong, Kailash Budhathoki, Taeho Kim +2
Mixture-of-Experts (MoE) layers increase model capacity without proportionally increasing arithmetic, but their sparse expert computation is difficult to execute efficiently during…
cs.RO2026
Causal Reward World Models: Zero-shot Reward Design for Automated Skill Generation
Yang Yang, Yuchuang Tong, Zhengtao Zhang +6
Automated Reward Design (ARD) aims to replace manual reward engineering in reinforcement learning with language-driven reward function synthesis. However, existing approaches based…