Natural Questions

66 papers with code • 2 benchmarks • 4 datasets

This task has no description! Would you like to contribute one?


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.