retrievalaware
Retrievalaware, or retrieval-aware, is a term used to describe systems, components, or models that explicitly account for the outcome of information retrieval when making decisions or being trained.
In retrieval-aware designs, the quality and characteristics of retrieved results (relevance, novelty, coverage, latency) are treated
Contexts for retrieval-aware approaches include information retrieval, knowledge-intensive natural language processing, question answering, search engines, and
Common methods encompass joint optimization of retriever and reader components, differentiable retrieval modules, retrieval-conditioned loss functions,
Challenges facing retrieval-aware approaches include defining appropriate retrieval quality metrics, balancing speed and accuracy, evaluating end-to-end
See also: retrieval-augmented generation, differentiable retrieval, knowledge-grounded NLP. Notes: the term is variably used in research