WORC improves multi-agent LLM reasoning to 82.2% average accuracy by predicting and compensating for the weakest agent via targeted extra sampling rather than uniform reinforcement.
Grey wolf optimizer,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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IWSO is a new metaheuristic using matchmaker-guided elite influence and adaptive elimination-reinitialization to achieve faster convergence and higher solution quality than GA, PSO, DE, and CS on high-dimensional benchmark functions.
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Weak-Link Optimization for Multi-Agent Reasoning and Collaboration
WORC improves multi-agent LLM reasoning to 82.2% average accuracy by predicting and compensating for the weakest agent via targeted extra sampling rather than uniform reinforcement.
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Indian Wedding System Optimization (IWSO): A Novel Socially Inspired Metaheuristic with Operational Design and Analysis
IWSO is a new metaheuristic using matchmaker-guided elite influence and adaptive elimination-reinitialization to achieve faster convergence and higher solution quality than GA, PSO, DE, and CS on high-dimensional benchmark functions.