output
20232026
most citedEvaluating gesture generation in a large-scale open challenge: The GENEA Challenge 2022

26 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

5 papers

cs.DC2026

MegaScale-Omni: A Hyper-Scale, Workload-Resilient System for MultiModal LLM Training in Production

Chunyu Xue, Yangrui Chen, Jianyu Jiang +14

As the foundational component of versatile AI applications, training an multimodal large language model (MLLM) relies on multimodal datasets with dynamic modality mixture proportio…

cs.DC2026

LAER-MoE: Load-Adaptive Expert Re-layout for Efficient Mixture-of-Experts Training

Xinyi Liu, Yujie Wang, Fangcheng Fu +4

Expert parallelism is vital for effectively training Mixture-of-Experts (MoE) models, enabling different devices to host distinct experts, with each device processing different inp…

physics.chem-ph2025

Accelerated Machine Learning Force Field for Predicting Thermal Conductivity of Organic Liquids

Wei Feng, Siyuan Liu, Hongyi Wang +11

The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, an…

cs.RO2025

Learning Vision-Driven Reactive Soccer Skills for Humanoid Robots

Yushi Wang, Changsheng Luo, Penghui Chen +7

Humanoid soccer poses a representative challenge for embodied intelligence, requiring robots to coordinate agile locomotion with unreliable visual perception in dynamic environment…

cs.HC2023★ 26 cited

Evaluating gesture generation in a large-scale open challenge: The GENEA Challenge 2022

Taras Kucherenko, Pieter Wolfert, Youngwoo Yoon +4

This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to bui…