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Delft University of Technology
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The competition reveals that many LLM evaluations may be fundamentally flawed due to undetected data contamination, challenging the validity of current benchmarks.
A new evaluation framework reveals that current assessments of LLM-powered agents often misrepresent their true capabilities in real-world software development.
Agent-generated code is more likely to be reworked or removed entirely, suggesting current AI coding tools may increase code churn despite boosting initial contribution rates.
