138 citations · 297 across the 9 of their papers we have counts for
14 papers
ToTTo: A Controlled Table-To-Text Generation Dataset
Ankur P. Parikh, Xuezhi Wang, Sebastian Gehrmann +4
We present ToTTo, an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of…
Differentiable Reasoning over a Virtual Knowledge Base
Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran +3
We consider the task of answering complex multi-hop questions using a corpus as a virtual knowledge base (KB). In particular, we describe a neural module, DrKIT, that traverses tex…
PubMedQA: A Dataset for Biomedical Research Question Answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu +2
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts. The task of PubMedQA is to answer research questions with yes/no/maybe (e…
Learning to Deceive with Attention-Based Explanations
Danish Pruthi, Mansi Gupta, Bhuwan Dhingra +2
Attention mechanisms are ubiquitous components in neural architectures applied to natural language processing. In addition to yielding gains in predictive accuracy, attention weigh…
Handling Divergent Reference Texts when Evaluating Table-to-Text Generation
Bhuwan Dhingra, Manaal Faruqui, Ankur Parikh +3
Automatically constructed datasets for generating text from semi-structured data (tables), such as WikiBio, often contain reference texts that diverge from the information in the c…
Combating Adversarial Misspellings with Robust Word Recognition
Danish Pruthi, Bhuwan Dhingra, Zachary C. Lipton
To combat adversarial spelling mistakes, we propose placing a word recognition model in front of the downstream classifier. Our word recognition models build upon the RNN semi-char…