Internship for Retriever LLM Evaluation Test on Electrical Drive Test Data

Summary

Beschreibung In a LLM-powered retrieval-augmented generation (RAG) system, retriever models impact the final answer generation quality of LLM. As a part of post-training of search agent for electrical drive test document, the performance of retriever models as well as the functionability of reranker models need to be investigated in a standard RAG framework. This internship focuses on experiments in comparing and evaluating the performance limits of retriever models across various factors: parameter, size, combination with re-ranking models, etc. on both public datasets and private data. The project can only be provided as internship to be conducted full-time in 9 weeks according to FSPO of MSEI, BSEI and other equivalent degree programs. Your task: • Cleansing of open-source datasets and private data • Configuration of RAG system with various retriever models • Building experiment platform and perform experiments • Collecting results and analysis Voraussetzungen • Interest in Artificial Intelligence, Large Language Models, and Agent-based Systems • Basic Python programming skills • Experience in LLM projects is welcome • MSEI, BSEI and other equivalent degree programs