3 papers
cs.CV2025
ClimaOoD: Improving Anomaly Segmentation via Physically Realistic Synthetic Data
Yuxing Liu, Zheng Li, Huanhuan Liang +3
Anomaly segmentation seeks to detect and localize unknown or out-of-distribution (OoD) objects that fall outside predefined semantic classes a capability essential for safe autonom…
cs.SE2025
Prompt Alchemy: Automatic Prompt Refinement for Enhancing Code Generation
Sixiang Ye, Zeyu Sun, Guoqing Wang +4
Code generation has emerged as a key task to automate software development by converting high-level descriptions into executable code. Large language models (LLMs) excel at this bu…
cs.SE2025
LLMs are Bug Replicators: An Empirical Study on LLMs' Capability in Completing Bug-prone Code
Liwei Guo, Sixiang Ye, Zeyu Sun +6
Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, the training data used to develop these models often contain a significant amount…