29 citations · 46 across the 8 of their papers we have counts for
8 papers
PonyEval: Evaluating LLM-Based Program Repair for Capability-Safe and Actor-Oriented Pony Software
Bang Xie, Hao Liu, Zhenyu Shi +8
Repository-level issue-resolution benchmarks have made executable evaluation central to software-engineering agents, but their language coverage remains concentrated in mainstream…
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 +7
Domain generalization (DG) aims to improve the generalizability of computer vision models toward distribution shifts. The mainstream DG methods predominantly focus on learning doma…
DGMamba: Domain Generalization via Generalized State Space Model
Shaocong Long, Qianyu Zhou, Xiangtai Li +5
Domain generalization~(DG) aims at solving distribution shift problems in various scenes. Existing approaches are based on Convolution Neural Networks (CNNs) or Vision Transformers…
Rethinking Domain Generalization: Discriminability and Generalizability
Shaocong Long, Qianyu Zhou, Chenhao Ying +2
Domain generalization(DG) endeavors to develop robust models that possess strong generalizability while preserving excellent discriminability. Nonetheless, pivotal DG techniques te…
Diverse Target and Contribution Scheduling for Domain Generalization
Shaocong Long, Qianyu Zhou, Chenhao Ying +2
Generalization under the distribution shift has been a great challenge in computer vision. The prevailing practice of directly employing the one-hot labels as the training targets…