23 citations · 130 across the 27 of their papers we have counts for
30 papers
LakeBench: Benchmarks for Data Discovery over Data Lakes
Kavitha Srinivas, Julian Dolby, Ibrahim Abdelaziz +6
Within enterprises, there is a growing need to intelligently navigate data lakes, specifically focusing on data discovery. Of particular importance to enterprises is the ability to…
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types
Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan +9
With the growing interest in large language models, the need for evaluating the quality of machine text compared to reference (typically human-generated) text has become focal atte…
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations
Achille Fokoue, Ibrahim Abdelaziz, Maxwell Crouse +5
Using reinforcement learning for automated theorem proving has recently received much attention. Current approaches use representations of logical statements that often rely on the…
Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning
Wenting Zhao, Ibrahim Abdelaziz, Julian Dolby +3
Dynamically typed languages such as Python have become very popular. Among other strengths, Python's dynamic nature and its straightforward linking to native code have made it the…
Expressive Reasoning Graph Store: A Unified Framework for Managing RDF and Property Graph Databases
Sumit Neelam, Udit Sharma, Sumit Bhatia +5
Resource Description Framework (RDF) and Property Graph (PG) are the two most commonly used data models for representing, storing, and querying graph data. We present Expressive Re…
CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases
Dung Thai, Srinivas Ravishankar, Ibrahim Abdelaziz +7
Knowledge bases (KBs) are often incomplete and constantly changing in practice. Yet, in many question answering applications coupled with knowledge bases, the sparse nature of KBs…
Large Scale Generation of Labeled Type Data for Python
Ibrahim Abdelaziz, Julian Dolby, Kavitha Srinivas
Recently, dynamically typed languages, such as Python, have gained unprecedented popularity. Although these languages alleviate the need for mandatory type annotations, types still…
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +22
Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily…
Learning to Transpile AMR into SPARQL
Mihaela Bornea, Ramon Fernandez Astudillo, Tahira Naseem +5
We propose a transition-based system to transpile Abstract Meaning Representation (AMR) into SPARQL for Knowledge Base Question Answering (KBQA). This allows us to delegate part of…
A Two-Stage Approach towards Generalization in Knowledge Base Question Answering
Srinivas Ravishankar, June Thai, Ibrahim Abdelaziz +5
Most existing approaches for Knowledge Base Question Answering (KBQA) focus on a specific underlying knowledge base either because of inherent assumptions in the approach, or becau…
A Scalable AutoML Approach Based on Graph Neural Networks
Mossad Helali, Essam Mansour, Ibrahim Abdelaziz +2
AutoML systems build machine learning models automatically by performing a search over valid data transformations and learners, along with hyper-parameter optimization for each lea…
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +21
Knowledge Base Question Answering (KBQA) tasks that in-volve complex reasoning are emerging as an important re-search direction. However, most KBQA systems struggle withgeneralizab…
Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion
Prithviraj Sen, Breno W. S. R. Carvalho, Ibrahim Abdelaziz +4
Recent interest in Knowledge Base Completion (KBC) has led to a plethora of approaches based on reinforcement learning, inductive logic programming and graph embeddings. In particu…
Can Machines Read Coding Manuals Yet? -- A Benchmark for Building Better Language Models for Code Understanding
Ibrahim Abdelaziz, Julian Dolby, Jamie McCusker +1
Code understanding is an increasingly important application of Artificial Intelligence. A fundamental aspect of understanding code is understanding text about code, e.g., documenta…
Generative Relation Linking for Question Answering over Knowledge Bases
Gaetano Rossiello, Nandana Mihindukulasooriya, Ibrahim Abdelaziz +4
Relation linking is essential to enable question answering over knowledge bases. Although there are various efforts to improve relation linking performance, the current state-of-th…
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…
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar +27
Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understandin…
Leveraging Semantic Parsing for Relation Linking over Knowledge Bases
Nandana Mihindukulasooriya, Gaetano Rossiello, Pavan Kapanipathi +6
Knowledgebase question answering systems are heavily dependent on relation extraction and linking modules. However, the task of extracting and linking relations from text to knowle…
HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map
Jameel Malik, Ibrahim Abdelaziz, Ahmed Elhayek +5
3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. The state-of-the-art methods directly regress 3D…
Neural Analogical Matching
Maxwell Crouse, Constantine Nakos, Ibrahim Abdelaziz +1
Analogy is core to human cognition. It allows us to solve problems based on prior experience, it governs the way we conceptualize new information, and it even influences our visual…
An Experimental Study of Formula Embeddings for Automated Theorem Proving in First-Order Logic
Ibrahim Abdelaziz, Veronika Thost, Maxwell Crouse +1
Automated theorem proving in first-order logic is an active research area which is successfully supported by machine learning. While there have been various proposals for encoding…
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 Toolkit for Generating Code Knowledge Graphs
Ibrahim Abdelaziz, Julian Dolby, Jamie McCusker +1
Knowledge graphs have been proven extremely useful in powering diverse applications in semantic search and natural language understanding. In this paper, we present GraphGen4Code,…
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…