#automated-testing2 articles

2 articles

AINeutralarXiv – CS AI · 6h ago4

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Biases in the Blind Spot: Detecting What LLMs Fail to Mention

Researchers have developed an automated pipeline to detect hidden biases in Large Language Models that don't appear in their reasoning explanations. The system discovered previously unknown biases like Spanish fluency and writing formality across seven LLMs in hiring, loan approval, and university admission tasks.

AINeutralarXiv – CS AI · 6h ago1

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QD-MAPPER: A Quality Diversity Framework to Automatically Evaluate Multi-Agent Path Finding Algorithms in Diverse Maps

Researchers developed QD-MAPPER, a framework using Quality Diversity algorithms and Neural Cellular Automata to automatically generate diverse maps for evaluating Multi-Agent Path Finding (MAPF) algorithms. This addresses the limitation of testing MAPF algorithms on fixed, human-designed maps that may not cover all scenarios and could lead to overfitting.