16 citations · 29 across the 5 of their papers we have counts for
5 papers · 1 filter
Learning to Guide a Saturation-Based Theorem Prover
Ibrahim Abdelaziz, Maxwell Crouse, Bassem Makni +8
Traditional automated theorem provers have relied on manually tuned heuristics to guide how they perform proof search. Recently, however, there has been a surge of interest in the…
Explainable Deep RDFS Reasoner
Bassem Makni, Ibrahim Abdelaziz, James Hendler
Recent research efforts aiming to bridge the Neural-Symbolic gap for RDFS reasoning proved empirically that deep learning techniques can be used to learn RDFS inference rules. Howe…
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…
Answering Science Exam Questions Using Query Rewriting with Background Knowledge
Ryan Musa, Xiaoyan Wang, Achille Fokoue +6
Open-domain question answering (QA) is an important problem in AI and NLP that is emerging as a bellwether for progress on the generalizability of AI methods and techniques. Much o…
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa +8
Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained…