5 papers
SWE-Milestone: Evaluating AI Agents on Continuous Software Evolution
Gangda Deng, Zhaoling Chen, Zhongming Yu +11
Real-world software must continuously evolve to meet ever-changing and open-ended requirements. AI agents, increasingly deployed as long-running systems, are now entrusted to drive…
Isolating Recurring Execution-Dependent Abnormal Patterns on NISQ Quantum Devices
Zhenyu Qi, Haotang Li, Mominul Islam +3
Quantum devices increasingly expose a fundamental gap between compiler-modeled noise and hardware execution. Today's compilers approximate noise as calibration-derived costs over g…
Tensor Algebraic Property Skeletons: Amplifying Property-Based Testing for AI Compilers
Yuxin Qiu, Ben Limpanukorn, Seongmin Lee +3
Deep learning (DL) compilers such as TVM and ONNX-MLIR lower tensor computation graphs into optimized executables for target backends. Testing these compilers has made substantial…
Finding Compiler-Platform Interaction Bugs in Deep Learning Pipelines via Cross-Layer Constraints
Yuxin Qiu, Jiyuan Wang, Ronak Badhe +3
The growing deployment of artificial intelligence (AI) necessitates robust deep learning (DL) compilers, such as TVM and ONNX-MLIR. These compilers take as input high-level AI mode…
PerfGen: Automated Performance Benchmark Generation for Big Data Analytics
Jiyuan Wang, Jason Teoh, Muhammand Ali Gulza +2
Many symptoms of poor performance in big data analytics such as computational skews, data skews, and memory skews are input dependent. However, due to the lack of inputs that can t…