Natural Questions

66 papers with code • 2 benchmarks • 4 datasets

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Libraries

Use these libraries to find Natural Questions models and implementations

Most implemented papers

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

huggingface/transformers 10 Nov 2019

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.

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

princeton-nlp/DensePhrases EACL 2021

Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge.

Relevance-guided Supervision for OpenQA with ColBERT

stanford-futuredata/ColBERT 1 Jul 2020

In much recent work, the retriever is a learned component that uses coarse-grained vector representations of questions and passages.

A BERT Baseline for the Natural Questions

google-research/language 24 Jan 2019

This technical note describes a new baseline for the Natural Questions.

Event Extraction by Answering (Almost) Natural Questions

xinyadu/eeqa EMNLP 2020

The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments.

AutoQA: From Databases To QA Semantic Parsers With Only Synthetic Training Data

stanford-oval/genie-toolkit EMNLP 2020

To demonstrate the generality of AutoQA, we also apply it to the Overnight dataset.

Generating Natural Questions About an Image

chingyaoc/vqg-tensorflow ACL 2016

There has been an explosion of work in the vision & language community during the past few years from image captioning to video transcription, and answering questions about images.

TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection

alexa/wqa_tanda AAAI 2020 2019

Additionally, we show that the transfer step of TANDA makes the adaptation step more robust to noise.

MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering

apple/ml-mkqa 30 Jul 2020

Progress in cross-lingual modeling depends on challenging, realistic, and diverse evaluation sets.