17 citations · 101 across the 17 of their papers we have counts for
4 papers · 1 filter
Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks
Pavan Kapanipathi, Veronika Thost, Siva Sankalp Patel +10
Textual entailment is a fundamental task in natural language processing. Most approaches for solving the problem use only the textual content present in training data. A few approa…
Path-Based Contextualization of Knowledge Graphs for Textual Entailment
Kshitij Fadnis, Kartik Talamadupula, Pavan Kapanipathi +3
In this paper, we introduce the problem of knowledge graph contextualization -- that is, given a specific NLP task, the problem of extracting meaningful and relevant sub-graphs fro…
A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving
Maxwell Crouse, Ibrahim Abdelaziz, Bassem Makni +7
Automated theorem provers have traditionally relied on manually tuned heuristics to guide how they perform proof search. Deep reinforcement learning has been proposed as a way to o…
High-Fidelity Vector Space Models of Structured Data
Maxwell Crouse, Achille Fokoue, Maria Chang +6
Machine learning systems regularly deal with structured data in real-world applications. Unfortunately, such data has been difficult to faithfully represent in a way that most mach…