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Bilibili-Evolved is a browser-based environment that functions as a web content modification engine. It operates as a user interface customization suite, allowing users to personalize their browsing experience by injecting custom logic and interface modifications directly into the Bilibili platform. The project distinguishes itself through a modular component architecture that organizes independent features into isolated units, which can be toggled or configured individually. It utilizes a user-script injection mechanism and a document mutation observer pattern to dynamically alter site asset

X-algorithm is a modular recommendation engine framework designed to orchestrate personalized content feeds. It functions as a machine learning ranking system that manages the end-to-end lifecycle of content delivery, from initial candidate retrieval to final display ordering. The system distinguishes itself through a multi-stage pipeline that integrates vector-based similarity search with transformer-based engagement prediction. By mapping user history and content features into high-dimensional embeddings, it performs rapid approximate nearest neighbor searches to identify relevant items. Th

Gorse is a personalized recommendation engine server and machine learning pipeline designed to suggest items to users based on their behavior and preferences. It operates as a distributed system that separates training, candidate generation, and serving nodes to support high-throughput workloads. The system utilizes a multi-stage recommendation pipeline to refine results through retrieval, scoring, and reranking. It generates personalized suggestions using collaborative filtering, matrix factorization, and item-to-item similarity models, while also providing non-personalized and fallback reco