newsResearchers introduced RAISE, a training-free evolutionary framework that improves text-to-image generation by adaptively refining outputs based on prompt complexity. The system achieves state-of-the-art alignment scores while reducing computational costs by 30-80% compared to existing methods.
Researchers introduce CEMMA, a co-evolutionary framework for improving AI safety alignment in multimodal large language models. The system uses evolving adversarial attacks and adaptive defenses to create more robust AI systems that better resist jailbreak attempts while maintaining functionality.
Researchers have developed Lilium, an automated evolutionary method that uses AI to improve skull-face overlay accuracy in forensic identification of skeletal remains. The system employs a Differential Evolution algorithm with 3D cone-based representation to model soft-tissue variability and outperforms existing state-of-the-art methods.