EfficientRAG: Efficient Retriever for Multi-Hop Question Answering
Retrieval-augmented generation (RAG) methods encounter difficulties when addressing complex questions like multi-hop queries. While iterative retrieval methods improve performance by gathering additional information, current approaches often rely on multiple calls of large language models (LLMs). In this paper, we introduce EfficientRAG, an efficient retriever for multi-hop question answering. EfficientRAG iteratively generates new queries without the need for LLM calls at each iteration and filters out irrelevant information. Experimental results demonstrate that EfficientRAG surpasses existing RAG methods on three open-domain multi-hop question-answering datasets.
Code (1)
Tasks
Multi-hop Question AnsweringQuestion AnsweringRAGRetrievalRetrieval-augmented GenerationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
A Comprehensive Evaluation of Transformer-Based Question Answering Models and RAG-Enhanced Design
Transformer-based models have advanced the field of question answering, but multi-hop reasoning, where answers require combining evidence across multiple passages, remains difficult. This paper presents a comprehensive e…
Multi-hop Question AnsweringSilver Retriever: Advancing Neural Passage Retrieval for Polish Question Answering
Modern open-domain question answering systems often rely on accurate and efficient retrieval components to find passages containing the facts necessary to answer the question. Recently, neural retrievers have gained popu…
Open-Domain Question AnsweringPassage RetrievalQuestion AnsweringRetrievalAnswering Complex Open-domain Questions Through Iterative Query Generation
It is challenging for current one-step retrieve-and-read question answering (QA) systems to answer questions like "Which novel by the author of 'Armada' will be adapted as a feature film by Steven Spielberg?" because the…
Information RetrievalQuestion AnsweringRetrievalA Multimodal Dense Retrieval Approach for Speech-Based Open-Domain Question Answering
Speech-based open-domain question answering (QA over a large corpus of text passages with spoken questions) has emerged as an important task due to the increasing number of users interacting with QA systems via speech in…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Open-Domain Question AnsweringPassage Retrieval+4Distilling Knowledge from Reader to Retriever for Question Answering
The task of information retrieval is an important component of many natural language processing systems, such as open domain question answering. While traditional methods were based on hand-crafted features, continuous r…
Information RetrievalKnowledge DistillationOpen-Domain Question AnsweringQuestion Answering+1