Saizheng Zhang

HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

2018 · arXiv (Cornell University)

Existing question answering (QA) datasets fail to train QA systems to perform complex reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) …

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.

Personalizing Dialogue Agents: I have a dog, do you have pets too?

2018 · arXiv (Cornell University)

Chit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating. In this work we present the task of making chit-chat more engaging …

Assessing Factoid Question-Answer Generation for Portuguese (Short Paper)

2017 · arXiv (Cornell University)

We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers. We show how to train the model using a combination of supervised and reinforcement learning. After teacher forcing for standard …