June Yang

According to our database, June Yang authored at least 10 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Guess-Verify-Refine: Data-Aware Top-K for Sparse-Attention Decoding on Blackwell via Temporal Correlation.

Long Cheng, Ritchie Zhao, Timmy Liu, Mindy Li, Xianjie Qiao, Kefeng Duan, Yu-Jung Chen, Xiaoming Chen, Bita Darvish Rouhani, June Yang

CoRR, April, 2026

DWDP: Distributed Weight Data Parallelism for High-Performance LLM Inference on NVL72.

Wanqian Li, Jintao Peng, Zongfei Jing, Tianyu Zhang, Ze Long, Xianjie Qiao, Xiaoming Chen, Dongxu Yang, Kefeng Duan, June Yang

CoRR, April, 2026

Scalable Training of Mixture-of-Experts Models with Megatron Core.

Zijie Yan, Hongxiao Bai, Xin Yao, Dennis Liu, Tong Liu, Hongbin Liu, Pingtian Li, Evan Wu, Shiqing Fan, Li Tao, Robin Zhang, Yuzhong Wang, Shifang Xu, Jack Chang, Xuwen Chen, Kunlun Li, Yan Bai, Gao Deng, Nan Zheng, Vijay Anand Korthikanti, Abhinav Khattar, Ethan He, Soham Govande, Sangkug Lym, Zhongbo Zhu, Qi Zhang, Haochen Yuan, Xiaowei Ren, Deyu Fu, Tailai Ma, Shunkang Zhang, Jiang Shao, Ray Wang, Vasudevan Rengasamy, Rachit Garg, Santosh Bhavani, Xipeng Li, Chandler Zhou, David Wu, Yingcan Wei, Ashwath Aithal, Michael Andersch, Mohammad Shoeybi, Jiajie Yao, June Yang

CoRR, March, 2026

2025

BroRL: Scaling Reinforcement Learning via Broadened Exploration.

Jian Hu, Mingjie Liu, Ximing Lu, Fang Wu, Zaïd Harchaoui, Shizhe Diao, Yejin Choi, Pavlo Molchanov, June Yang, Jan Kautz, Yi Dong

CoRR, October, 2025

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training.

Mingjie Liu, Shizhe Diao, Jian Hu, Ximing Lu, Xin Dong, Hao Zhang, Alexander Bukharin, Shaokun Zhang, Jiaqi Zeng, Makesh Narsimhan Sreedhar, Gerald Shen, David Mosallanezhad, Di Zhang, Jonas Yang, June Yang, Oleksii Kuchaiev, Guilin Liu, Zhiding Yu, Pavlo Molchanov, Yejin Choi, Jan Kautz, Yi Dong

CoRR, July, 2025

MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core.

Dennis Liu, Zijie Yan, Xin Yao, Tong Liu, Vijay Korthikanti, Evan Wu, Shiqing Fan, Gao Deng, Hongxiao Bai, Jianbin Chang, Ashwath Aithal, Michael Andersch, Mohammad Shoeybi, Jiajie Yao, Chandler Zhou, David Wu, Xipeng Li, June Yang

CoRR, April, 2025

2024

Llama 3 Meets MoE: Efficient Upcycling.

Aditya Vavre, Ethan He, Dennis Liu, Zijie Yan, June Yang, Nima Tajbakhsh, Ashwath Aithal

CoRR, 2024

2023

Aligning Language Models with Offline Reinforcement Learning from Human Feedback.

Jian Hu, Li Tao, June Yang, Chandler Zhou

CoRR, 2023

HyperGef: A Framework Enabling Efficient Fusion for Hypergraph Neural Network on GPUs.

Zhongming Yu, Guohao Dai, Shang Yang, Genghan Zhang, Hengrui Zhang, Feiwen Zhu, June Yang, Jishen Zhao, Yu Wang

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

FastDimeNet++: Training DimeNet++ in 22 minutes.

Feiwen Zhu, Michal Futrega, Han Bao, Sukru Burc Eryilmaz, Fei Kong, Kefeng Duan, Xinnian Zheng, Nimrod Angel, Matthias Jouanneaux, Maximilian Stadler, Michal Marcinkiewicz, Fung Xie, June Yang, Michael Andersch

Proceedings of the 52nd International Conference on Parallel Processing, 2023