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Open-Domain Question Answering

31 papers with code · Natural Language Processing
Subtask of Question Answering

Open-domain question answering is the task of question answering on open-domain datasets such as Wikipedia.

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Latest papers with code

Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering

30 Apr 2020xwhan/ProQA

In this work, we propose a simple and resource-efficient method to pretrain the paragraph encoder.

INFORMATION RETRIEVAL OPEN-DOMAIN QUESTION ANSWERING

20
30 Apr 2020

AmbigQA: Answering Ambiguous Open-domain Questions

22 Apr 2020shmsw25/AmbigQA

In this paper, we introduce AmbigQA, a new open-domain question answering task which involves predicting a set of question-answer pairs, where every plausible answer is paired with a disambiguated rewrite of the original question.

OPEN-DOMAIN QUESTION ANSWERING

27
22 Apr 2020

ktrain: A Low-Code Library for Augmented Machine Learning

19 Apr 2020amaiya/ktrain

We present ktrain, a low-code Python library that makes machine learning more accessible and easier to apply.

IMAGE CLASSIFICATION LINK PREDICTION NODE CLASSIFICATION OPEN-DOMAIN QUESTION ANSWERING TEXT CLASSIFICATION

376
19 Apr 2020

Dense Passage Retrieval for Open-Domain Question Answering

10 Apr 2020deepset-ai/haystack

Open-domain question answering relies on efficient passage retrieval to select candidate contexts, where traditional sparse vector space models, such as TF-IDF or BM25, are the de facto method.

OPEN-DOMAIN QUESTION ANSWERING

288
10 Apr 2020

REALM: Retrieval-Augmented Language Model Pre-Training

10 Feb 2020deepset-ai/haystack

Language model pre-training has been shown to capture a surprising amount of world knowledge, crucial for NLP tasks such as question answering.

LANGUAGE MODELLING OPEN-DOMAIN QUESTION ANSWERING

288
10 Feb 2020

Break It Down: A Question Understanding Benchmark

31 Jan 2020allenai/Break

Understanding natural language questions entails the ability to break down a question into the requisite steps for computing its answer.

OPEN-DOMAIN QUESTION ANSWERING READING COMPREHENSION SEMANTIC PARSING VISUAL QUESTION ANSWERING

38
31 Jan 2020

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

10 Nov 2019facebookresearch/DPR

We introduce an approach for open-domain question answering (QA) that retrieves and reads a passage graph, where vertices are passages of text and edges represent relationships that are derived from an external knowledge base or co-occurrence in the same article.

OPEN-DOMAIN QUESTION ANSWERING READING COMPREHENSION TEXT MATCHING

65
10 Nov 2019

Contextualized Sparse Representations for Real-Time Open-Domain Question Answering

ICLR 2020 dmis-lab/covidsearch

Open-domain question answering can be formulated as a phrase retrieval problem, in which we can expect huge scalability and speed benefit but often suffer from low accuracy due to the limitation of existing phrase representation models.

INFORMATION RETRIEVAL OPEN-DOMAIN QUESTION ANSWERING

27
07 Nov 2019

Language Models as Knowledge Bases?

IJCNLP 2019 facebookresearch/LAMA

Recent progress in pretraining language models on large textual corpora led to a surge of improvements for downstream NLP tasks.

LANGUAGE MODELLING OPEN-DOMAIN QUESTION ANSWERING

536
03 Sep 2019