3 papers
cs.CR2026
SecReason: Vulnerability Detection and In-Stream Self-Repair for LLM Code Generation
Ruidong Han, Zhensu Sun, Chengyan Ma +4
Large language models (LLMs) may introduce security vulnerabilities into generated code, which can persist into production when verification focuses on functional correctness. Exis…
cs.LG2026
Improving Model Performance by Adapting the KGE Metric to Account for System Non-Stationarity
M Jawad, HV Gupta, YH Wang +3
Geoscientific systems tend to be characterized by pronounced temporal non-stationarity, arising from seasonal and climatic variability in hydrometeorological drivers, and from natu…
cs.LG2026
Process-Aware AI for Rainfall-Runoff Modeling: A Mass-Conserving Neural Framework with Hydrological Process Constraints
Mohammad A. Farmani, Hoshin V. Gupta, Ali Behrangi +3
Machine learning models can achieve high predictive accuracy in hydrological applications but often lack physical interpretability. The Mass-Conserving Perceptron (MCP) provides a…