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What Breaks When LLMs Code? Characterizing Operational Safety Failures of Agentic Code Assistants
An empirical study of 547 real-world operational safety failures in LLM-based coding agents, revealing a taxonomy of 33 risk types and showing that over 65% of incidents arise during routine bug fixing and configuration tasks.
Alif Al Hasan, Sumon Biswas
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Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relations
We propose a unified framework using metamorphic relations for systematic bias evaluation and mitigation in black-box LLMs.
Sina Salimian, Gias Uddin, Sumon Biswas, Henry Leung
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