2 papers
cs.LG2025
Autoencoder-based General Purpose Representation Learning for Customer Embedding
Jan Henrik Bertrand, David B. Hoffmann, Jacopo Pio Gargano +2
Recent advances in representation learning have successfully leveraged the underlying domain-specific structure of data across various fields. However, representing diverse and com…
cs.IR2024
Meta Knowledge for Retrieval Augmented Large Language Models
Laurent Mombaerts, Terry Ding, Adi Banerjee +3
Retrieval Augmented Generation (RAG) is a technique used to augment Large Language Models (LLMs) with contextually relevant, time-critical, or domain-specific information without a…