3 papers
cs.AI2026
HRBench: Benchmarking and Understanding Thinking-Mode Switch Strategies in Hybrid-Reasoning LLMs
Yansong Ning, Mianpeng Liu, Jingwen Ye +2
Hybrid-reasoning large language models (LLMs) expose explicit controls over reasoning effort, allowing users or systems to trade off answer quality against inference cost. However,…
cs.DC2026
TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training
Chenhao Ye, Huaizheng Zhang, Mingcong Han +11
Modern LLM reinforcement learning (RL) workloads require a highly efficient weight transfer system to scale training across heterogeneous computational resources. However, existing…
cs.CV2025
Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
Weidong Zhang, Pak Lun Kevin Ding, Huan Liu
Lightweight vision classification models such as MobileNet, ShuffleNet, and EfficientNet are increasingly deployed in mobile and embedded systems, yet their performance has been pr…