QUADRo: Dataset and Models for QUestion-Answer Database Retrieval
An effective paradigm for building Automated Question Answering systems is the re-use of previously answered questions, e.g., for FAQs or forum applications. Given a database (DB) of question/answer (q/a) pairs, it is possible to answer a target question by scanning the DB for similar questions. In this paper, we scale this approach to open domain, making it competitive with other standard methods, e.g., unstructured document or graph based. For this purpose, we (i) build a large scale DB of 6.3M q/a pairs, using public questions, (ii) design a new system based on neural IR and a q/a pair reranker, and (iii) construct training and test data to perform comparative experiments with our models. We demonstrate that Transformer-based models using (q,a) pairs outperform models only based on question representation, for both neural search and reranking. Additionally, we show that our DB-based approach is competitive with Web-based methods, i.e., a QA system built on top the BING search engine, demonstrating the challenge of finding relevant information. Finally, we make our data and models available for future research.
Code (0)
등록된 구현이 없습니다.
Tasks
Question AnsweringRerankingRetrievalMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
FAQ Retrieval using Query-Question Similarity and BERT-Based Query-Answer Relevance
Frequently Asked Question (FAQ) retrieval is an important task where the objective is to retrieve an appropriate Question-Answer (QA) pair from a database based on a user's query. We propose a FAQ retrieval system that c…
Information RetrievalQuestion SimilarityRetrievalAnswering Ambiguous Questions with a Database of Questions, Answers, and Revisions
Many open-domain questions are under-specified and thus have multiple possible answers, each of which is correct under a different interpretation of the question. Answering such ambiguous questions is challenging, as it …
Passage RetrievalQuestion AnsweringRetrievalFine-Grained Table Retrieval Through the Lens of Complex Queries
Enabling question answering over tables and databases in natural language has become a key capability in the democratization of insights from tabular data sources. These systems first require retrieval of data that is re…
Open-Domain Question AnsweringTable RetrievalRetrieval Augmented Generation for Domain-specific Question Answering
Question answering (QA) has become an important application in the advanced development of large language models. General pre-trained large language models for question-answering are not trained to properly understand th…
Language ModelingLanguage ModellingLarge Language ModelQuestion Answering+2Learning Representations for Zero-Shot Retrieval over Structured Data
Large Scale Question-Answering systems today are widely used in downstream applications such as chatbots and conversational dialogue agents. Typically, such systems consist of an Answer Passage retrieval layer coupled wi…
Passage RetrievalQuestion AnsweringReading ComprehensionRetrieval