About

Most current question answering datasets frame the task as reading comprehension where the question is about a paragraph or document and the answer often is a span in the document. The Machine Reading group at UCL also provides an overview of reading comprehension tasks.

Benchmarks

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Subtasks

Datasets

Greatest papers with code

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

NeurIPS 2020 huggingface/transformers

With the success of language pretraining, it is highly desirable to develop more efficient architectures of good scalability that can exploit the abundant unlabeled data at a lower cost.

READING COMPREHENSION TEXT CLASSIFICATION

Robust Reading Comprehension with Linguistic Constraints via Posterior Regularization

16 Nov 2019huggingface/pytorch-pretrained-BERT

In this paper, we address the over-confidence issue and the over-sensitivity issue existing in current RC models simultaneously with the help of external linguistic knowledge.

MACHINE READING COMPREHENSION

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

10 Nov 2019huggingface/transformers

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

XLNet: Generalized Autoregressive Pretraining for Language Understanding

NeurIPS 2019 huggingface/transformers

With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.

DOCUMENT RANKING HUMOR DETECTION LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION QUESTION ANSWERING READING COMPREHENSION SENTIMENT ANALYSIS TEXT CLASSIFICATION

Language Models are Unsupervised Multitask Learners

Preprint 2019 huggingface/transformers

Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.

 Ranked #1 on Language Modelling on enwik8 (using extra training data)

4 COMMON SENSE REASONING DATA-TO-TEXT GENERATION DOCUMENT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION MULTI-TASK LEARNING QUESTION ANSWERING READING COMPREHENSION

AllenNLP: A Deep Semantic Natural Language Processing Platform

WS 2018 allenai/allennlp

This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding.

NATURAL LANGUAGE UNDERSTANDING READING COMPREHENSION SEMANTIC ROLE LABELING

Reading Wikipedia to Answer Open-Domain Questions

ACL 2017 facebookresearch/ParlAI

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article.

OPEN-DOMAIN QUESTION ANSWERING READING COMPREHENSION

Embracing data abundance: BookTest Dataset for Reading Comprehension

4 Oct 2016facebookresearch/ParlAI

We show that training on the new data improves the accuracy of our Attention-Sum Reader model on the original CBT test data by a much larger margin than many recent attempts to improve the model architecture.

READING COMPREHENSION