activity
20242026
most citedOn the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis

5 citations · 16 across the 15 of their papers we have counts for

collaborators

17 papers

cs.CV2026

Do CNNs Internally Represent Real and Fake Images Differently? A Hidden-Layer Analysis

Moumita Sen Sarma, Pascal Hitzler, Eugene Y. Vasserman

Fake/synthetic images are increasingly prevalent, but it remains unclear whether Convolutional Neural Networks (CNNs) process real and fake images in the same internal manner. This…

q-bio.NC2025

On the Analogy between Human Brain and LLMs: Spotting Key Neurons in Grammar Perception

Sanaz Saki Norouzi, Mohammad Masjedi, Pascal Hitzler

Artificial Neural Networks, the building blocks of AI, were inspired by the human brain's network of neurons. Over the years, these networks have evolved to replicate the complex c…

cs.CY2025

An Ontology for Representing Curriculum and Learning Material

Antrea Christou, Chris Davis Jaldi, Joseph Zalewski +3

Educational, learning, and training materials have become extremely commonplace across the Internet. Yet, they frequently remain disconnected from each other, fall into platform si…

cs.DB2025

The KnowWhereGraph: A Large-Scale Geo-Knowledge Graph for Interdisciplinary Knowledge Discovery and Geo-Enrichment

Rui Zhu, Cogan Shimizu, Shirly Stephen +25

Global challenges such as food supply chain disruptions, public health crises, and natural hazard responses require access to and integration of diverse datasets, many of which are…

cs.AI2025

From Field Data to Global Food Systems Intelligence: A Semantic Graph Framework for Sustainable Wheat Production

Nirmal Gelal, Aastha Gautam, Soheil Abadifard +15

In response to the growing need for structured, interoperable agricultural data, this paper presents the Sustainable Wheat Production Datahub, a modular, graph-based framework that…

cs.AI2024★ 2 cited

Accelerating Knowledge Graph and Ontology Engineering with Large Language Models

Cogan Shimizu, Pascal Hitzler

Large Language Models bear the promise of significant acceleration of key Knowledge Graph and Ontology Engineering tasks, including ontology modeling, extension, modification, popu…

cs.AI2024★ 3 cited

Ontology Population using LLMs

Sanaz Saki Norouzi, Adrita Barua, Antrea Christou +4

Knowledge graphs (KGs) are increasingly utilized for data integration, representation, and visualization. While KG population is critical, it is often costly, especially when data…

cs.CL2024

Knowledge in Triples for LLMs: Enhancing Table QA Accuracy with Semantic Extraction

Hossein Sholehrasa, Sanaz Saki Norouzi, Pascal Hitzler +1

Integrating structured knowledge from tabular formats poses significant challenges within natural language processing (NLP), mainly when dealing with complex, semi-structured table…

cs.AI2024

The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphs

Shirly Stephen, Mitchell Faulk, Krzysztof Janowicz +10

Geospatial Knowledge Graphs (GeoKGs) have become integral to the growing field of Geospatial Artificial Intelligence. Initiatives like the U.S. National Science Foundation's Open K…

cs.AI2024

The KnowWhereGraph Ontology

Cogan Shimizu, Shirly Stephe, Adrita Barua +21

KnowWhereGraph is one of the largest fully publicly available geospatial knowledge graphs. It includes data from 30 layers on natural hazards (e.g., hurricanes, wildfires), climate…

cs.LG2024

ConceptLens: from Pixels to Understanding

Abhilekha Dalal, Pascal Hitzler

ConceptLens is an innovative tool designed to illuminate the intricate workings of deep neural networks (DNNs) by visualizing hidden neuron activations. By integrating deep learnin…

cs.CL2024★ 1 cited

They Look Like Each Other: Case-based Reasoning for Explainable Depression Detection on Twitter using Large Language Models

Mohammad Saeid Mahdavinejad, Peyman Adibi, Amirhassan Monadjemi +1

Depression is a common mental health issue that requires prompt diagnosis and treatment. Despite the promise of social media data for depression detection, the opacity of employed…

cs.LG2024

Error-margin Analysis for Hidden Neuron Activation Labels

Abhilekha Dalal, Rushrukh Rayan, Pascal Hitzler

Understanding how high-level concepts are represented within artificial neural networks is a fundamental challenge in the field of artificial intelligence. While existing literatur…

cs.AI2024★ 5 cited

On the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis

Abhilekha Dalal, Rushrukh Rayan, Adrita Barua +3

A major challenge in Explainable AI is in correctly interpreting activations of hidden neurons: accurate interpretations would help answer the question of what a deep learning syst…

cs.AI2024★ 3 cited

Towards Complex Ontology Alignment using Large Language Models

Reihaneh Amini, Sanaz Saki Norouzi, Pascal Hitzler +1

Ontology alignment, a critical process in the Semantic Web for detecting relationships between different ontologies, has traditionally focused on identifying so-called "simple" 1-t…

cs.AI2024

Commonsense Ontology Micropatterns

Andrew Eells, Brandon Dave, Pascal Hitzler +1

The previously introduced Modular Ontology Modeling methodology (MOMo) attempts to mimic the human analogical process by using modular patterns to assemble more complex concepts. T…

cs.CL2024★ 2 cited

On the Psychology of GPT-4: Moderately anxious, slightly masculine, honest, and humble

Adrita Barua, Gary Brase, Ke Dong +2

We subject GPT-4 to a number of rigorous psychometric tests and analyze the results. We find that, compared to the average human, GPT-4 tends to show more honesty and humility, and…