3 citations · 4 across the 5 of their papers we have counts for
5 papers
Agentic Model Checking
Youcheng Sun, Jiawen Liu, Daniel Kroening +1
Verifying LLM-generated systems code is hard: bugs are prevalent, formal specifications are missing, and safety contracts are encoded implicitly at call sites rather than enforced…
TIDAL: Recovering Temporal Phase for Cloud Block Storage Placement from LLM-Derived Semantics
Difan Tan, Changlin Wan, Jiawen Liu +2
Cloud Virtual Disk (CVD) placement in Cloud Block Storage (CBS) is critical for resource efficiency and performance isolation. Existing schemes prioritize spatial load balancing by…
FLAME: A Self-Adaptive Auto-labeling System for Heterogeneous Mobile Processors
Jie Liu, Jiawen Liu, Zhen Xie +1
How to accurately and efficiently label data on a mobile device is critical for the success of training machine learning models on mobile devices. Auto-labeling data on mobile devi…
Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices
Jie Liu, Jiawen Liu, Wan Du +1
Training deep learning models on mobile devices recently becomes possible, because of increasing computation power on mobile hardware and the advantages of enabling high user exper…
Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training
Jiawen Liu, Dong Li, Gokcen Kestor +1
Training neural network often uses a machine learning framework such as TensorFlow and Caffe2. These frameworks employ a dataflow model where the NN training is modeled as a direct…