However, many previous works studied textual and relational retrieval tasks as separate topics.

Large language models (LLMs) have rapidly improved text embeddings for a growing array of natural-language processing tasks.

Gaussian mixture models (GMMs) are fundamental to machine learning due to their flexibility as approximating densities. However, uncertainty quantification of GMMs remains a challenge as differential entropy lacks a closed form.