Search Results for author: Bassem Makni

Found 7 papers, 1 papers with code

Learning to Guide a Saturation-Based Theorem Prover

no code implementations7 Jun 2021 Ibrahim Abdelaziz, Maxwell Crouse, Bassem Makni, Vernon Austil, Cristina Cornelio, Shajith Ikbal, Pavan Kapanipathi, Ndivhuwo Makondo, Kavitha Srinivas, Michael Witbrock, Achille Fokoue

In addition, to the best of our knowledge, TRAIL is the first reinforcement learning-based approach to exceed the performance of a state-of-the-art traditional theorem prover on a standard theorem proving benchmark (solving up to 17% more problems).

Automated Theorem Proving reinforcement-learning +1

Explainable Deep RDFS Reasoner

no code implementations10 Feb 2020 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.

Machine Translation Translation

Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks

no code implementations5 Nov 2019 Pavan Kapanipathi, Veronika Thost, Siva Sankalp Patel, Spencer Whitehead, Ibrahim Abdelaziz, Avinash Balakrishnan, Maria Chang, Kshitij Fadnis, Chulaka Gunasekara, Bassem Makni, Nicholas Mattei, Kartik Talamadupula, Achille Fokoue

A few approaches have shown that information from external knowledge sources like knowledge graphs (KGs) can add value, in addition to the textual content, by providing background knowledge that may be critical for a task.

Knowledge Graphs Natural Language Inference

Answering Science Exam Questions Using Query Rewriting with Background Knowledge

no code implementations15 Sep 2018 Ryan Musa, Xiaoyan Wang, Achille Fokoue, Nicholas Mattei, Maria Chang, Pavan Kapanipathi, Bassem Makni, Kartik Talamadupula, Michael Witbrock

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.

Information Retrieval Multiple-choice +3

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