52 citations · 52 across the 4 of their papers we have counts for
9 papers
FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information
Rami Aly, Zhijiang Guo, Michael Schlichtkrull +5
Fact verification has attracted a lot of attention in the machine learning and natural language processing communities, as it is one of the key methods for detecting misinformation…
Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets
Esma Balkir, Masha Naslidnyk, Dave Palfrey +1
Bilinear models such as DistMult and ComplEx are effective methods for knowledge graph (KG) completion. However, they require large batch sizes, which becomes a performance bottlen…
Large Scale Question Paraphrase Retrieval with Smoothed Deep Metric Learning
Daniele Bonadiman, Anjishnu Kumar, Arpit Mittal
The goal of a Question Paraphrase Retrieval (QPR) system is to retrieve equivalent questions that result in the same answer as the original question. Such a system can be used to u…
Generating Token-Level Explanations for Natural Language Inference
James Thorne, Andreas Vlachos, Christos Christodoulopoulos +1
The task of Natural Language Inference (NLI) is widely modeled as supervised sentence pair classification. While there has been a lot of work recently on generating explanations of…
Learning When Not to Answer: A Ternary Reward Structure for Reinforcement Learning based Question Answering
Fréderic Godin, Anjishnu Kumar, Arpit Mittal
In this paper, we investigate the challenges of using reinforcement learning agents for question-answering over knowledge graphs for real-world applications. We examine the perform…
The Fact Extraction and VERification (FEVER) Shared Task
James Thorne, Andreas Vlachos, Oana Cocarascu +2
We present the results of the first Fact Extraction and VERification (FEVER) Shared Task. The task challenged participants to classify whether human-written factoid claims could be…