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hkevin01 / eeg-rag

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EEG-RAG is a Retrieval-Augmented Generation (RAG) system specifically designed for electroencephalography (EEG) research. It enables researchers, clinicians, and data scientists to ask natural language questions about EEG literature and receive evidence-based answers with proper citations.

gpu-computing lang-python nlp-tools status-experimental ai-ml-portfolio scope-enterprise framework-numpy framework-pandas framework-huggingface framework-pytorch framework-scikit-learn ai-ml-portfolio-rag gpu-deep-learning gpu-rag gpu-nlp gdl-bio-neuro
  • Updated May 19, 2026
  • Python

hkevin01 / pddl-instruct-lcot

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This project implements PDDL-INSTRUCT with Logical Chain-of-Thought (LCoT), a novel approach to improve Large Language Model (LLM) performance on automated planning tasks. The system enhances planning capabilities through:

gpu-computing status-active lang-python nlp-tools generative-ai ai-ml-portfolio status-stable scope-micro framework-numpy framework-matplotlib framework-pandas framework-huggingface framework-pytorch framework-scikit-learn ai-ml-portfolio-llm gpu-deep-learning gpu-llm gpu-nlp
  • Updated May 19, 2026
  • Python

hkevin01 / csneps-robotics-inference

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CSNePS Knowledge Graph Service is a production-ready enterprise system that bridges symbolic AI reasoning with modern ontology engineering. The system combines CSNePS (Cognitive Systems for Natural language Processing and Structured information) - a powerful semantic network reasoning engine - with comprehensive OWL ontology support, advanced graph

status-active lang-java status-finished nlp-tools generative-ai gpu-inference ai-ml-portfolio scope-small ai-ml-portfolio-llm gpu-deep-learning gpu-llm gpu-nlp
  • Updated May 19, 2026
  • Java

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