5 papers
HerAgent: Rethinking the Automated Environment Deployment via Hierarchical Test Pyramid
Xiang Li, Siyu Lu, Federica Sarro +2
Automated software environment setup is a prerequisite for testing, debugging, and reproducing failures, yet remains challenging in practice due to complex dependencies, heterogene…
Prometheus: Towards Long-Horizon Codebase Navigation for Repository-Level Problem Solving
Yue Pan, Zimin Chen, Siyu Lu +8
Large Language Models (LLMs) have shown remarkable capabilities in automating software engineering tasks, spurring the emergence of coding agents that scaffold LLMs with external t…
You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation
Yutong Bian, Xianhao Lin, Yupeng Xie +11
Large Language Models (LLMs) and code agents in software development are rapidly evolving from generating isolated code snippets to producing full-fledged software applications wit…
H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity
Wei Guo, Siyuan Lu, Yiqi Tong +5
Different from existing federated fine-tuning (FFT) methods for foundation models, hybrid heterogeneous federated fine-tuning (HHFFT) is an under-explored scenario where clients ex…
Unleashing the Potential of Large Language Models as Prompt Optimizers: Analogical Analysis with Gradient-based Model Optimizers
Xinyu Tang, Xiaolei Wang, Wayne Xin Zhao +3
Automatic prompt optimization is an important approach to improving the performance of large language models (LLMs). Recent research demonstrates the potential of using LLMs as pro…