30 citations · 46 across the 10 of their papers we have counts for
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cs.LG2025★ 1 cited
Muon is Scalable for LLM Training
Jingyuan Liu, Jianlin Su, Xingcheng Yao +25
Recently, the Muon optimizer based on matrix orthogonalization has demonstrated strong results in training small-scale language models, but the scalability to larger models has not…
cs.LG2025
MoBA: Mixture of Block Attention for Long-Context LLMs
Enzhe Lu, Zhejun Jiang, Jingyuan Liu +22
Scaling the effective context length is essential for advancing large language models (LLMs) toward artificial general intelligence (AGI). However, the quadratic increase in comput…
cs.LG2018★ 30 cited
Natural Environment Benchmarks for Reinforcement Learning
Amy Zhang, Yuxin Wu, Joelle Pineau
While current benchmark reinforcement learning (RL) tasks have been useful to drive progress in the field, they are in many ways poor substitutes for learning with real-world data.…