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Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models
Recent advances in prompting techniques and multi-agent systems for Large Language Models (LLMs) have produced increasingly complex approaches.
The Tyranny of Possibilities in the Design of Task-Oriented LLM Systems: A Scoping Survey
The paper discusses the implications of this lens, for the cross-pollination of research between LLM prompting and LLM-based multi-agent systems; and also, for the generation of synthetic training data based on existing prompting techniques in research.
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