Reader
Related Papers
Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
AbstractThis paper considers the reading comprehension task in which multiple documents are given as input. Prior work has shown that a pipeline of retriever, reader, and reranker can improve the …...
Don’t Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering
AbstractMost approaches to Open-Domain Question Answering consist of a light-weight retriever that selects a set of candidate passages, and a computationally expensive reader that examines the passages to identify the …...
Relevance-guided Supervision for OpenQA with ColBERT
AbstractSystems for Open-Domain Question Answering (OpenQA) generally depend on a retriever for finding candidate passages in a large corpus and a reader for extracting answers from those passages. In much …...
monoQA: Multi-Task Learning of Reranking and Answer Extraction for Open-Retrieval Conversational Question Answering
AbstractTo address the Conversational Question Answering (ORConvQA) task, previous work has considered an effective three-stage architecture, consisting of a retriever, a reranker, and a reader to extract the answers. In …...