Examples of using different retrievers in LangChain, including Wikipedia, Vector Store, MMR, MultiQuery, and Contextual Compression retrievers. Demonstrates how to fetch relevant context for semantic search, Q&A, summarization, and retrieval-augmented generation (RAG).

Examination of whether LLMs can maintain consistency over extended multiple text generation for 10 medical personas. 5 novel plausibility metrics proposed, and an ontology of common LLM errors.

Structure‑aware RAG platform with semantic search and citations.

A system based on the study by Aranzamendez, Bolito, and Rafe (2024) titled "An Enhancement of Content-based Filtering Applied in Movie Recommendation System."