Xingdi Yuan

Counting to Explore and Generalize in Text-based Games

2018 · arXiv (Cornell University)

We propose a recurrent RL agent with an episodic exploration mechanism that helps discovering good policies in text-based game environments. We show promising results on a set of generated text-based games of varying difficulty where …

Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives

2019 · arXiv (Cornell University)

This paper tackles the problem of reading comprehension over long narratives where documents easily span over thousands of tokens. We propose a curriculum learning (CL) based Pointer-Generator framework for reading/sampling over large documents, enabling diverse …

NewsQA: A Machine Comprehension Dataset

2017

We present NewsQA, a challenging machine comprehension dataset of over 100,000 human-generated question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting of spans …

Machine Comprehension by Text-to-Text Neural Question Generation

2017

Xingdi Yuan, Tong Wang, Caglar Gulcehre, Alessandro Sordoni, Philip Bachman, Saizheng Zhang, Sandeep Subramanian, Adam Trischler. Proceedings of the 2nd Workshop on Representation Learning for NLP. 2017.

A Joint Model for Question Answering and Question Generation

2017 · arXiv (Cornell University)

We propose a generative machine comprehension model that learns jointly to ask and answer questions based on documents. The proposed model uses a sequence-to-sequence framework that encodes the document and generates a question (answer) given …

NewsQA: A Machine Comprehension Dataset

2016 · arXiv (Cornell University)

We present NewsQA, a challenging machine comprehension dataset of over 100,000 human-generated question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting of spans …