We present a privacy-aware query generation approach that identifies sensitive information in the knowledge graph and masks it before sending anything to the LLM. Our experiments indicate that this preserves query quality while preventing sensitive data from leaving your system.
With a vision similar to ActivityPub and the Fediverse, but focused on model federation, we propose ModelFed and Modelverse, a decentralized ecosystem that enables collaborative modeling across different platforms.
We propose a new Domain-Specific Language to precisely define the sustainability aspects of an ML model (including the energy costs for its different tasks) that can be exported as an extended Model Card
With this bpmn extension you can model how humans and agents (and also agent communities) should collaborate to accomplish a given task
Is low-code changing the way that researchers publish in the modeling field?
A novel pipeline that uses Large Language Models (LLMs) to convert UI mock-ups – either hand-drawn or digitally designed – into user interface models for a robust code-generation
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