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Systematic reuse of models in Digital Twin ecosystems can now be achieved with a framework that clarifies compatibility and integration challenges, improving interoperability across diverse systems.
Iterative LLM feedback can significantly improve research software quality, revealing critical trade-offs that challenge conventional development practices.
Transforming legacy scientific applications into cloud-native workflows is now feasible without losing original functionality, thanks to an innovative AI-assisted framework.
LLMCrater transforms the way we generate FAIR metadata by continuously enriching it throughout the research lifecycle, not just at publication time.
