SGTO-MAS applies Gorilla Troops Optimization to formulate multi-agent LLM coordination as a constrained optimization problem, reporting average performance of 0.5281, consensus 0.8764, risk 0.3000, and 4.04 agents selected across 500 runs.
Malf: A multi-agent llm framework for intelligent fuzzing of industrial control protocols,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
FuzzPilot implements plateau-triggered recipe validation for AFL++ but reports no statistically significant coverage gains and zero promotions of model-proposed recipes on the saturated cJSON target.
citing papers explorer
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FuzzPilot: Plateau-Triggered Recipe Validation for Structured Text Fuzzing
FuzzPilot implements plateau-triggered recipe validation for AFL++ but reports no statistically significant coverage gains and zero promotions of model-proposed recipes on the saturated cJSON target.