Model-driven Prompt Engineering
We propose a DSL for prompt engineering to define platform-independent prompts that can later be adapted to provide good quality outputs in any target AI system
Low-code vs model-driven: are they the same?
I don’t see any significant technical novelty in the low-code movement. But I do not see this as being negative. More the opposite. Read why I think the low-code movement represents a great opportunity for the modeling community.
A Modeling Editor and Code Generator for message-driven architectures with AsyncAPI
AsyncAPI allows you to define Message-Driven and event-driven APIs in a machine-readable format. Our AsyncAPI toolkit helps you to model and create AsyncAPI specifications and automatically generate code from them.
Robust Hashing for Efficient Model Similarity estimation
We present a novel robust hashing mechanism for models. Robust hashing algorithms (i.e. hashing algorithms that generate similar outputs from similar input data) are useful as a key building block in intellectual property protection, authenticity assessment and fast comparison and retrieval solutions
Yet Another Model Transformation Language (YAMTL): Enabling Model Transformation from Java/Xtend
Yet Another Model Transformation Language (YAMTL) provides a fresh approach to model transformation by favouring agility, interoperability, reuse, expressivity and performance. With YAMTL, model transformations can be easily integrated within JVM programs and model...The low-code handbook
Modeling: all you need to know
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