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cs.SE2026
Beyond Correctness: Enhancing Architectural Reasoning in Code LLMs via Scalable Labeling with Agentic Judgment
Kirill Vasilevski, Ximing Dong, Benjamin Rombaut +8
LLMs have substantially improved software engineering yet real-world development requires architectural understanding. Such understanding is prohibitively expensive to label manual…
cs.SE2025
SWE-Effi: Re-Evaluating Software AI Agent System Effectiveness Under Resource Constraints
Zhiyu Fan, Kirill Vasilevski, Dayi Lin +6
The advancement of large language models (LLMs) and code agents has demonstrated significant potential to assist software engineering (SWE) tasks, such as autonomous issue resoluti…
cs.SE2025
The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware)
Kirill Vasilevski, Benjamin Rombaut, Gopi Krishnan Rajbahadur +10
Foundation Models (FMs) such as Large Language Models (LLMs) are reshaping the software industry by enabling FMware, systems that integrate these FMs as core components. In this KD…