SymRAG adaptively routes queries through neuro-symbolic, neural, or hybrid paths based on complexity and system load, ensuring efficient and accurate RAG for diverse QA tasks.
Resource-efficient LLM distillation: Improving sustainability and reducing computational costs of Large Language Models in financial analytics through knowledge distillation.
A lightweight pre-inference gate for resource-efficient AI agents.
A memory-efficient C++20 web crawler designed for extreme scalability. Implements probabilistic URL deduplication (Bloom Filter) to minimize RAM footprint and features a non-blocking asynchronous I/O loop. Engineered with a strict focus on RAII, thread safety, and graceful resource management.
Claude Code plugin that prevents unnecessary file creation through smart policies and modular SKILLs. Chat-first approach with contextual analysis for cleaner codebases.
Open-source sustainability skillsets for AI agents, designed for environmental measurement, energy and resource efficiency, waste reduction, sustainability reporting, and evidence-based operational improvement.
Code, processed data, and visualizations supporting the global material flow analysis of sugarcane and sugar beet.
The source codes for bachelor's thesis
Ein Machine-Learning-Projekt zur automatischen Unterscheidung von Web- und Strickstoffen für Textilrecycling. Enthält eigenen Demo-Datensatz, Annotation-Guide, Modell-Training und Auswertung.
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