An article discussing the use of embeddings in natural language processing, focusing on comparing open source and closed source embedding models for semantic search, including techniques like clustering and re-ranking.
Re-ranking is integral to retrieval pipelines, but implementation methods vary. We introduce rerankers, a Python library offering a unified interface for common re-ranking approaches.
The Towards Data Science team highlights recent articles on the rise of open-source LLMs, ethical considerations with chatbots, potential manipulation of LLM recommendations, and techniques for temperature scaling and re-ranking in generative AI.
