⚡️A Blazing-Fast Python Library for Ranking Evaluation, Comparison, and Fusion 🐍
Repository with basic information about Rank Aggregation Problem.
Learning Latent Semantic Representations of Paintings for Personalized Recommendation
Easy to use rank aggregation software for recommendation systems
Question-Answering (QA) system powered by Retrieval-Augmented Generation (RAG). The system leverages advanced methods such as Rank Fusion and Cascading Retrieval for optimized document retrieval and contextual QA generation.
RAG pipeline for medical question-answering. Fuses lexical and dense retrieval (MedCPT, Contriever, Specter + FAISS) with OpenAI, Gemini, and HuggingFace LLMs. Supports iterative multi-round reasoning, strict typing, structured observability, and a clean layered architecture
Implementation of various vector rank fusion algorithms
Rank fusion and reranking
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