Yu Wang

Reinforcement learning (RL) has demonstrated immense potential in advancing artificial general intelligence, agentic intelligence, and embodied intelligence. However, the inherent heterogeneity and dynamicity of RL workflows often lead to low hardware utilization and slow training on existing sys...

Modern reinforcement learning (RL) workloads, powering large language models, long‑horizon reasoning, and agentic systems, exhibit extreme dynamicity due to heavy‑tailed rollouts, irregular multi‑turn tool interactions, and time‑varying bottlenecks. Static resource allocations in today’s distribu...

TapeOBS is an archive storage service offered by Huawei Cloud, which delivers high cost-efficiency by leveraging tape to store large volumes of archived data. Although tape boasts a low total cost of ownership, its inherent characteristics (e.g., a limited number of drives within a tape library)...

Small Language Models (SLMs) provide computational advantages in resource-constrained environments, yet memory limitations remain a critical bottleneck for edge device deployment. A substantial portion of SLMs’ memory footprint stems from vocabulary-related components, particularly embeddings and...