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.
Code, processed data, and visualizations supporting the global material flow analysis of sugarcane and sugar beet.
The source codes for bachelor's thesis
Open-source sustainability skillsets for AI agents, designed for environmental measurement, energy and resource efficiency, waste reduction, sustainability reporting, and evidence-based operational improvement.
Claude Code plugin that prevents unnecessary file creation through smart policies and modular SKILLs. Chat-first approach with contextual analysis for cleaner codebases.
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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