4 papers
OdinEval: A Reproducible Benchmark for LLM-Based Program Repair in the Odin Programming Language
Bang Xie, Hao Liu, Zhiyuan Peng +8
Repository-level repair benchmarks still center on a few mainstream languages, leaving systems languages such as Odin largely untested. We present OdinEval, a reproducible benchmar…
AppEval: A Unified Benchmark for LLM-Based Mobile Application Repair in ArkTS, Swift, and Kotlin
Bang Xie, Hao Liu, Zhenyu Shi +11
Repository-level LLM agents are typically evaluated on projects whose tests run on the build host. It remains unclear whether their repairs survive the mobile build-install-launch-…
Domain Generalization via Discrete Codebook Learning
Shaocong Long, Qianyu Zhou, Xikun Jiang +3
Domain generalization (DG) strives to address distribution shifts across diverse environments to enhance model's generalizability. Current DG approaches are confined to acquiring r…
Generative Classifier for Domain Generalization
Shaocong Long, Qianyu Zhou, Xiangtai Li +5
Domain generalization (DG) aims to improve the generalizability of computer vision models toward distribution shifts. The mainstream DG methods focus on learning domain invariance,…