Publications

Are Large Language Models Good Temporal Graph Learners? Permalink

Shenyang Huang, Alipanah Parviz, Emma Kondrup, Zachary Yang, Zifeng Ding, Michael Bronstein, Reihaneh Rabbany, Guillaume Rabusseau ...

It’s the Thought that Counts: Evaluating the Attempts of Frontier LLMs to Persuade on Harmful Topics Permalink

Matthew Kowal, Jasper Timm, J. Godbout, Thomas H Costello, A. Arechar, Gordon Pennycook, David Rand, Adam Gleave, Kellin Pelrine ...

Weak Supervision for Real World Graphs Permalink

Pratheeksha Nair, Reihaneh Rabbany Paper Abstract Node classification in real...

Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection Permalink

Zachary Yang, Domenico Tullo, Reihaneh Rabbany Paper Abstract Toxicity detect...

Rendering-Aware Reinforcement Learning for Vector Graphics Generation Permalink

Juan A. Rodriguez, Haotian Zhang, Abhay Puri, Aarash Feizi, Rishav Pramanik, Pascal Wichmann, Arnab Mondal, Mohammad Reza Samsami, Rabiul Awal, Perouz Taslak...

Accidental Misalignment: Fine-Tuning Language Models Induces Unexpected Vulnerability Permalink

Punya Syon Pandey, Samuel Simko, Kellin Pelrine, Zhijing Jin Paper Abstract A...

The Structural Safety Generalization Problem Permalink

Julius Broomfield, Tom Gibbs, Ethan Kosak-Hine, George Ingebretsen, Tia Nasir, Jason Zhang, Reihaneh Iranmanesh, Sara Pieri, Reihaneh Rabbany, Kellin Pelrine...

Can Go AIs Be Adversarially Robust? Permalink

Tom Tseng, Euan McLean, Kellin Pelrine, T. T. Wang, Adam Gleave AAAI Conference on Artificial Intelligence Paper ...

Scaling Trends for Data Poisoning in LLMs Permalink

Dillon Bowen, Brendan Murphy, Will Cai, David Khachaturov, Adam Gleave, Kellin Pelrine AAAI Conference on Artificial Intelligence ...

From Intuition to Understanding: Using AI Peers to Overcome Physics Misconceptions Permalink

Ruben Weijers, Denton Wu, Hannah Betts, Tamara Jacod, Yuxiang Guan, Vidya Sujaya, Kushal Dev, Toshali Goel, William Delooze, Reihaneh Rabbany, Ying Wu, J. Go...

PairBench: Are Vision-Language Models Reliable at Comparing What They See? Permalink

Aarash Feizi, Sai Rajeswar, Adriana Romero-Soriano, Reihaneh Rabbany, Valentina Zantedeschi, Spandana Gella, Joao Monteiro ...

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding Permalink

Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang, Suyuchen Wang, Chao Wang, Aarash Feizi, Akshay Kalkunte Suresh, Abhay Puri, Xiangru Jian, Pierre-Andr’e Noel, S...

BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks Permalink

Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan...

Online Influence Campaigns: Strategies and Vulnerabilities Permalink

Andreea Musulan, Veronica Xia, Ethan Kosak-Hine, Tom Gibbs, Vidya Sujaya, Reihaneh Rabbany, J. Godbout, Kellin Pelrine arXiv.org ...

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks Permalink

Juan Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte, Franccois Savard, Ahmed Masry, Shravan Nayak, R...

Epistemic Integrity in Large Language Models Permalink

Bijean Ghafouri, Shahrad Mohammadzadeh, James Zhou, Pratheeksha Nair, Jacob-Junqi Tian, Mayank Goel, Reihaneh Rabbany, J. Godbout, Kellin Pelrine ...

A Guide to Misinformation Detection Datasets Permalink

Data is a barrier to reliable misinformation detection solutions. To address this, we curated the largest collection of (mis)information datasets in the lite...

FairLoRA: Unpacking Bias Mitigation in Vision Models with Fairness-Driven Low-Rank Adaptation Permalink

Rohan Sukumaran, Aarash Feizi, Adriana Romero-Sorian, G. Farnadi Paper Abstrac...

Hallucination Detox: Sensitive Neuron Dropout (SeND) for Large Language Model Training Permalink

Shahrad Mohammadzadeh, Juan David Guerra, Marco Bonizzato, Reihaneh Rabbany, G. Farnadi Paper ...

A Simulation System Towards Solving Societal-Scale Manipulation Permalink

In this paper, we present a multi-agent simulator based on Deepmind’s Concordia, a software library for LLM-based multi-agent simulations of real world human...

Emerging Vulnerabilities in Frontier Models: Multi-Turn Jailbreak Attacks Permalink

Tom Gibbs, Ethan Kosak-Hine, George Ingebretsen, Jason Zhang, Julius Broomfield, Sara Pieri, Reihaneh Iranmanesh, Reihaneh Rabbany, Kellin Pelrine arXiv.org...

Web Retrieval Agents for Evidence-Based Misinformation Detection Permalink

We demonstrated an effective two LLM agent architecture for misinformation detection and fact-checking. It can increase the macro F1 of misinformation detect...

Data Poisoning in LLMs: Jailbreak-Tuning and Scaling Laws Permalink

Dillon Bowen, Brendan Murphy, Will Cai, David Khachaturov, A. Gleave, Kellin Pelrine Paper ...

UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs Permalink

Here we introduce the Unified Temporal Graph (UTG) framework, which integrates snapshot-based and event-based machine learning models for temporal graphs und...

Regional and Temporal Patterns of Partisan Polarization during the COVID-19 Pandemic in the United States and Canada Permalink

The COVID-19 pandemic sparked rigorous debate about public health measures online, as the timing and extent of interventions unfolded. This project evaluates...

Game On, Hate Off: A Study of Toxicity in Online Multiplayer Environments Permalink

While game companies are addressing the call to reduce toxicity and promote player health, the need to understand toxicity trends across time is important. W...

Can Go AIs be adversarially robust? Permalink

Tom Tseng, Euan McLean, Kellin Pelrine, T. T. Wang, A. Gleave arXiv.org Paper A...

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs Permalink

TGB 2.0 introduces a novel benchmarking framework for evaluating methods for predicting future links on Temporal Knowledge Graphs (TKGs) and Temporal Heterog...

Static graph approximations of dynamic contact networks for epidemic forecasting Permalink

In this work, we introduce new, more rigorous evaluation procedures for link prediction in dynamic graphs, addressing the challenges and real-world considera...

MiniMol: A Parameter-Efficient Foundation Model for Molecular Learning Permalink

Kerstin Kläser, Bla.zej Banaszewski, S. Maddrell-Mander, Callum McLean, Luis Müller, Alipanah Parviz, Shenyang Huang, Andrew W. Fitzgibbon arXiv.org ...

T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking Permalink

Detecting suspicious ads is challenging due to the sensitive, complex, and unlabeled nature of the data. T-Net addresses this as a weakly supervised graph le...

Temporal Graph Analysis with TGX Permalink

Here we introduce TGX, a Python package specifically designed for the analysis of temporal networks, addressing a gap in existing software libraries that pri...

Scavenging Hyena: Distilling Transformers into Long Convolution Models Permalink

Tokiniaina Raharison Ralambomihanta, Shahrad Mohammadzadeh, Mohammad Sami Nur Islam, Wassim Jabbour, Laurence Liang arXiv.org ...

Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation Permalink

LLMs struggle with hallucinations and overconfident predictions. Uncertainty quantification can improve their reliability and helpfulness. We proposed an unc...

Comparing GPT-4 and Open-Source Language Models in Misinformation Mitigation Permalink

Tyler Vergho, J. Godbout, Reihaneh Rabbany, Kellin Pelrine arXiv.org Paper Abst...

GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised Learning Permalink

Aarash Feizi, Randall Balestriero, Adriana Romero-Soriano, Reihaneh Rabbany arXiv.org Paper ...

Uncertainty Resolution in Misinformation Detection Permalink

Yury Orlovskiy, Camille Thibault, Anne Imouza, J. Godbout, Reihaneh Rabbany, Kellin Pelrine UNCERTAINLP Paper ...

Quantifying learning-style adaptation in effectiveness of LLM teaching Permalink

Ruben Weijers, Gabrielle Fidelis de Castilho, J. Godbout, Reihaneh Rabbany, Kellin Pelrine PERSONALIZE Paper ...

An Evaluation of Language Models for Hyperpartisan Ideology Detection in Persian Twitter Permalink

While LLMs have demonstrated how effective they can be for tasks in the English language, such as detecting social media users’ political ideology, their per...

Exploiting Novel GPT-4 APIs Permalink

Kellin Pelrine, Mohammad Taufeeque, Michal Zajkac, Euan McLean, A. Gleave arXiv.org Paper ...

Exhaustive Evaluation of Dynamic Link Prediction Permalink

Farimah Poursafaei, Reihaneh Rabbany 2023 IEEE International Conference on Data Mining Workshops (ICDMW) Paper ...

SWEET : Weakly Supervised Person Name Extraction for Fighting Human Trafficking Permalink

SWEET is a weak supervision pipeline for extracting person names from noisy escort ads, addressing the challenge of limited labeled data. SWEET combines rule...

Towards Detecting Contextual Real-Time Toxicity for In-Game Chat Permalink

A simple and scalable model that reliably detects toxic content in real-time for a line of chat by including chat history and metadata. ToxBuster consistentl...

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets Permalink

D. Beaini, Shenyang Huang, Joao Alex Cunha, Gabriela Moisescu-Pareja, Oleksandr Dymov, Sam Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Muller, Jama...

Party Prediction for Twitter Permalink

Partisanship has increasingly become a major point of contention in public discourse online, and as a result, researchers have developed a variety of methods...

Open, Closed, or Small Language Models for Text Classification? Permalink

Hao Yu, Zachary Yang, Kellin Pelrine, J. Godbout, Reihaneh Rabbany arXiv.org Paper ...

Towards Temporal Edge Regression: A Case Study on Agriculture Trade Between Nations Permalink

Lekang Jiang, Caiqi Zhang, Farimah Poursafaei, Shenyang Huang arXiv.org Paper A...

Temporal Graph Benchmark for Machine Learning on Temporal Graphs Permalink

In this paper, we introduce the Temporal Graph Benchmark (TGB), a comprehensive collection of large-scale, diverse datasets designed for the realistic, repro...

Graph learning with programmatic weak supervision Permalink

Pratheeksha Nair Canadian AI Paper Abstract None

Better Bridges Between Model and Real World Permalink

Kellin Pelrine Canadian AI Paper Abstract To build better machine learning sol...

When does Continuous Learning for BERT make sense? Permalink

Zachary Yang Canadian AI Paper Abstract None

Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4 Permalink

We propose focusing on generalization, uncertainty, and how to leverage recent large language models, in order to create more practical tools to evaluate inf...

ToxBuster: In-game Chat Toxicity Buster with BERT Permalink

Zachary Yang, Yasmine Maricar, M. Davari, Nicolas Grenon-Godbout, Reihaneh Rabbany arXiv.org Paper ...

Fast and Attributed Change Detection on Dynamic Graphs with Density of States Permalink

We introduce a novel spectral method called Scalable Change Point Detection (SCPD) to address the limitations of current solutions in detecting anomalous cha...

Social Media as a Vector for Escort Ads:A Study on OnlyFans advertisements on Twitter Permalink

Maricarmen Arenas, Pratheeksha Nair, Reihaneh Rabbany, G. Farnadi Web Science Conference Paper ...

DisKeyword: Tweet Corpora Exploration for Keyword Selection Permalink

Sacha Lévy, Reihaneh Rabbany Web Search and Data Mining Paper Abstract How to ...

DeltaShield: Information Theory for Human- Trafficking Detection Permalink

Catalina Vajiac, Meng-Chieh Lee, Aayushi Kulshrestha, Sacha Lévy, Namyong Park, Andreas M. Olligschlaeger, Cara Jones, Reihaneh Rabbany, C. Faloutsos ACM Tr...

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Permalink

Dominic Masters, Josef Dean, K. Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, D. Beker, A. Fitzgibbon, Shenyang Huang, Ladislav Rampášek,...

Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs Permalink

Shenyang Huang, Samy Coulombe, Yasmeen Hitti, Reihaneh Rabbany, Guillaume Rabusseau ACM Transactions on Knowledge Discovery from Data ...

SWEET - Weakly Supervised Person Name Extraction for Fighting Human Trafficking Permalink

Javin Liu, Hao Yu, Vidya Sujaya, Pratheeksha Nair, Kellin Pelrine, Reihaneh Rabbany Conference on Empirical Methods in Natural Language Processing ...

Unveiling Identity Biases in Toxicity Detection : A Game-Focused Dataset and Reactivity Analysis Approach Permalink

Identity biases arise commonly from annotated datasets, can be propagated in language models and can cause further harm to marginal groups. Existing bias ben...

Adversarial Policies Beat Superhuman Go AIs Permalink

T. T. Wang, A. Gleave, Nora Belrose, Tom Tseng, Joseph Miller, Kellin Pelrine, Michael Dennis, Yawen Duan, V. Pogrebniak, S. Levine, Stuart Russell Internat...

TRAFFIC BOARD : Digital Spatio-Temporal Pinboard for Human Trafficking Detection Permalink

Catalina Vajiac, Duen Horng, †. Chau, Andreas M. Olligschlaeger, Pratheeksha Nair, Meng-Chieh Lee, M. Cazzolato, Reihaneh Rabbany, Christos Faloutsos ...

TrafficVis: Visualizing Organized Activity and Spatio-Temporal Patterns for Detecting and Labeling Human Trafficking Permalink

TrafficVis is an interactive interface for detecting and labeling human trafficking (HT) in clusters of escort ads. Developed with domain experts, it uses ad...

Active Keyword Selection to Track Evolving Topics on Twitter Permalink

Sacha L’evy, Farimah Poursafaei, Kellin Pelrine, Reihaneh Rabbany 2022 IEEE International Conference on Data Mining Workshops (ICDMW) ...

Revisiting Hotels-50K and Hotel-ID Permalink

Aarash Feizi, Arantxa Casanova, Adriana Romero-Soriano, Reihaneh Rabbany arXiv.org Paper ...

Towards Better Evaluation for Dynamic Link Prediction Permalink

In this work, we introduce new, more rigorous evaluation procedures for link prediction in dynamic graphs, addressing the challenges and real-world considera...

PCR-based Evaluation of Human Papillomavirus Genotypes in Oral Lichen Planus Permalink

A. Vijayan, Arvind Muthukrishnan, Aparna Nair, S. Fathima, Pratheeksha Nair, J. Roshan Journal of Pharmacy and Bioallied Sciences ...

VisPaD: Visualization and Pattern Discovery for Fighting Human Trafficking Permalink

Pratheeksha Nair, Yifei Li, Catalina Vajiac, Andreas M. Olligschlaeger, Meng-Chieh Lee, Namyong Park, Duen Horng Chau, C. Faloutsos, Reihaneh Rabbany, Chieh ...

The Winners and Losers of Rental Tribunals Permalink

Andreea Musulan Social Science Research Network Paper Abstract None

Extracting Person Names from User Generated Text: Named-Entity Recognition for Combating Human Trafficking Permalink

Yifei Li, Pratheeksha Nair, Kellin Pelrine, Reihaneh Rabbany Findings Paper Abs...

A Strong Node Classification Baseline for Temporal Graphs Permalink

Here we introduce a robust and effective baseline method for node classification in temporal graphs, serving as a benchmark for evaluating more complex model...

Curating the Twitter Election Integrity Datasets for Better Online Troll Characterization Permalink

Albert Orozco, Reihaneh Rabbany LatinX in AI at Neural Information Processing Systems Conference 2021 Paper ...

Online Partisan Polarization of COVID-19 Permalink

Zachary Yang, Anne Imouza, Kellin Pelrine, Sacha Lévy, Jiewen Liu, Gabrielle Desrosiers-Brisebois, J. Godbout, A. Blais, Reihaneh Rabbany 2021 International...

Understanding Capacity Saturation in Incremental Learning Permalink

Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau Canadian Conference on AI Paper ...

Graph Attention Networks with Positional Embeddings Permalink

Liheng Ma, Reihaneh Rabbany, Adriana Romero-Soriano Pacific-Asia Conference on Knowledge Discovery and Data Mining Paper ...

The Surprising Performance of Simple Baselines for Misinformation Detection Permalink

While many sophisticated detection models have been proposed in the literature, they were often compared with older NLP baselines such as SVMs, CNNs, and LST...

INFOSHIELD: Generalizable Information-Theoretic Human-Trafficking Detection Permalink

INFOSHIELD is a scalable, parameter-free, and interpretable tool for detecting near-duplicate document clusters, with applications in human trafficking detec...

Efficient detection of online communities and social bot activity during electoral campaigns Permalink

L. Rheault, Andreea Musulan Journal of Information Technology & Politics Paper ...

RAFFIC V IS : Fighting Human Trafﬁcking through Visualization Permalink

Catalina Vajiac, Andreas M. Olligschlaeger, Yifei Li, Pratheeksha Nair, Meng-Chieh Lee, Namyong Park, Reihaneh Rabbany, Duen Horng Chau, C. Faloutsos ...

Few Shot Image Generation via Implicit Autoencoding of Support Sets Permalink

Shenyang Huang, Kuan-Chieh Jackson Wang, Alireza Makhzani Paper Abstract Rece...

Scalable Change Point Detection for Dynamic Graphs Permalink

Shenyang Huang, Guillaume Rabusseau, Reihaneh Rabbany Paper Abstract Real wor...

SigTran: Signature Vectors for Detecting Illicit Activities in Blockchain Transaction Networks Permalink

SigTran is an efficient graph-based method for identifying illicit nodes in blockchain networks. SigTran constructs a graph from blockchain transaction recor...

Graph Neural Networks Learn Twitter Bot Behaviour Permalink

Albert Orozco, Sacha Lévy, Reihaneh Rabbany LatinX in AI at Neural Information Processing Systems Conference 2020 Paper ...

ComplexDataLab at W-NUT 2020 Task 2: Detecting Informative COVID-19 Tweets by Attending over Linked Documents Permalink

Kellin Pelrine, Jacob Danovitch, Albert Orozco Camacho, Reihaneh Rabbany WNUT Paper ...

Contact Graph Epidemic Modelling of COVID-19 for Transmission and Intervention Strategies Permalink

Abby Leung, Xiaoye Ding, Shenyang Huang, Reihaneh Rabbany arXiv.org Paper Abstr...

Incorporating dynamic flight network in SEIR to model mobility between populations Permalink

In this paper, we introduce a significant enhancement to the standard SEIR (Susceptible, Exposed, Infectious, Recovered) epidemiological model by integrating...

Structure Aware Negative Sampling in Knowledge Graphs Permalink

Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, A. Bose Conference on Empirical Methods in Natural Language Processing ...

Global Surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model Permalink

Yue Li, Pratheeksha Nair, Zhi Wen, I. Chafi, A. Okhmatovskaia, G. Powell, Yannan Shen, D. Buckeridge ACM International Conference on Bioinformatics, Computa...

Explaining Support for COVID-19 Cell Phone Contact Tracing Permalink

L. Rheault, Andreea Musulan Canadian Journal of Political Science/Revue canadienne de science politique Paper ...

Laplacian Change Point Detection for Dynamic Graphs Permalink

Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany Knowledge Discovery and Data Mining Paper ...

Group Equivariant Deep Reinforcement Learning Permalink

Arnab Kumar Mondal, Pratheeksha Nair, Kaleem Siddiqi arXiv.org Paper Abstract ...

RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning Permalink

S. Alletto, Shenyang Huang, Vincent François-Lavet, Yohei Nakata, Guillaume Rabusseau arXiv.org Paper ...

Investigating the Role of Social Bots During the 2019 Canadian Election Permalink

L. Rheault, Andreea Musulan Paper Abstract Threats of social media manipulati...

Machine learning analysis of exome trios to contrast the genomic architecture of autism and schizophrenia Permalink

Sameer Sardaar, B. Qi, Alexandre Dionne‐Laporte, G. Rouleau, Reihaneh Rabbany, Y. Trakadis BMC Psychiatry Paper ...

Scaling up Simhash Permalink

Rameshwar Pratap, Anup Anand Deshmukh, Pratheeksha Nair, Anirudh Ravi Asian Conference on Machine Learning Paper ...

A Study on Active Learning for Graphs Permalink

Pratheeksha Nair, Zhi Wen Paper Abstract This is a comprehensive study of act...

SCG: Spotting Coordinated Groups in Social Media Permalink

Junhao Wang, Sacha Lévy, Ren Wang, Aayushi Kulshrestha, Guillaume Rabusseau, Reihaneh Rabbany Paper ...

SGP: Spotting Groups Polluting the Online Political Discourse Permalink

Junhao Wang, Sacha Lévy, Ren Wang, Aayushi Kulshrestha, Reihaneh Rabbany arXiv.org Paper ...

Neural Architecture Search for Class-incremental Learning Permalink

Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau arXiv.org Paper Abs...

Anomaly Detection with Joint Representation Learning of Content and Connection Permalink

Junhao Wang, Renhao Wang, Aayushi Kulshrestha, Reihaneh Rabbany arXiv.org Paper ...

Politicians in the line of fire: Incivility and the treatment of women on social media Permalink

L. Rheault, Erica Rayment, Andreea Musulan Research & Politics Paper Abstra...

A Faster Sampling Algorithm for Spherical k-means Permalink

Rameshwar Pratap, Anup Anand Deshmukh, Pratheeksha Nair, T. Dutt Asian Conference on Machine Learning Paper ...

A Scalable Clustering Algorithm for Serendipity in Recommender Systems Permalink

Anup Anand Deshmukh, Pratheeksha Nair, Shrisha Rao 2018 IEEE International Conference on Data Mining Workshops (ICDMW) Pap...

Social-Affiliation Networks: Patterns and the SOAR Model Permalink

D. Eswaran, Reihaneh Rabbany, A. Dubrawski, C. Faloutsos ECML/PKDD Paper Abstra...

Active Search of Connections for Case Building and Combating Human Trafficking Permalink

Reihaneh Rabbany, David Bayani, A. Dubrawski Knowledge Discovery and Data Mining Paper ...

Modular Networks for Validating Community Detection Algorithms Permalink

Justin Fagnan, Afra Abnar, Reihaneh Rabbany, Osmar R Zaiane arXiv.org Paper Abs...

A Note on the Unconditional Bias of the Nadaraya-Watson Regression Estimator Permalink

Kellin Pelrine Paper Abstract In this note we investigate the order of the un...

Assortativity: Proclivity Index for Attributed Networks (P RO N E ) Permalink

Reihaneh Rabbany, D. Eswaran, Artur W. Dubrawski, Christos Faloutsos Paper Abs...

Beyond Assortativity: Proclivity Index for Attributed Networks (ProNe) Permalink

Reihaneh Rabbany, D. Eswaran, A. Dubrawski, C. Faloutsos Pacific-Asia Conference on Knowledge Discovery and Data Mining Pa...

A General Clustering Agreement Index: For Comparing Disjoint and Overlapping Clusters Permalink

Reihaneh Rabbany, Osmar R Zaiane AAAI Conference on Artificial Intelligence Paper ...

PROCLIVITY PATTERNS IN ATTRIBUTED GRAPHS Permalink

Reihaneh Rabbany, D. Eswaran, C. Faloutsos, A. Dubrawski Paper Abstract Many ...

Generalization of clustering agreements and distances for overlapping clusters and network communities Permalink

Reihaneh Rabbany, Osmar R Zaiane Data mining and knowledge discovery Paper Abst...

Evaluation of Community Mining Algorithms in the Presence of Attributes Permalink

Reihaneh Rabbany, Osmar R Zaiane PAKDD Workshops Paper Abstract None

Generating Attributed Networks with Communities Permalink

C. Largeron, Pierre-Nicolas Mougel, Reihaneh Rabbany, Osmar R Zaiane PLoS ONE Paper ...

Community Dynamics: Event and Role Analysis in Social Network Analysis Permalink

Justin Fagnan, Reihaneh Rabbany, M. Takaffoli, Eric Verbeek, Osmar R Zaiane International Conference on Advanced Data Mining and Applications ...

Generalization of clustering agreements and distances for overlapping clusters and network communities Permalink

Reihaneh Rabbany, Osmar R Zaiane Data mining and knowledge discovery Paper Abst...

Community evolution prediction in dynamic social networks Permalink

M. Takaffoli, Reihaneh Rabbany, Osmar R Zaiane International Conference on Advances in Social Networks Analysis and Mining ...

SSRM: structural social role mining for dynamic social networks Permalink

Afra Abnar, M. Takaffoli, Reihaneh Rabbany, Osmar R Zaiane Social Network Analysis and Mining Paper ...

Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning Permalink

Siamak Ravanbakhsh, Reihaneh Rabbany, R. Greiner Neural Information Processing Systems Paper ...

Mining Large Scale Data from National Educational Achievement Tests A Case Study Permalink

Reihaneh Rabbany, Osmar R Zaiane, Samira ElAtia Paper Abstract Large scale an...

Collaborative Learning of Students in Online Discussion Forums: A Social Network Analysis Perspective Permalink

Reihaneh Rabbany, Samira ElAtia, M. Takaffoli, Osmar R Zaiane Paper Abstract ...

Communities validity: methodical evaluation of community mining algorithms Permalink

Reihaneh Rabbany, M. Takaffoli, Justin Fagnan, Osmar R Zaiane, R. Campello Social Network Analysis and Mining Paper ...

Incremental local community identification in dynamic social networks Permalink

M. Takaffoli, Reihaneh Rabbany, Osmar R Zaiane International Conference on Advances in Social Networks Analysis and Mining ...

Relative Validity Criteria for Community Mining Algorithms Synonyms Evaluation Permalink

Reihaneh Rabbany, Mansoreh Takaffoli, Justin Fagnan, Osmar R. Zäıane, R. Campello Paper ...

Relative Validity Criteria for Community Mining Algorithms Permalink

Reihaneh Rabbany, M. Takaffoli, Justin Fagnan, Osmar R Zaiane, R. Campello 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis an...

Social network analysis and mining to support the assessment of on-line student participation Permalink

Reihaneh Rabbany, M. Takaffoli, Osmar R Zaiane SKDD Paper Abstract There is a ...

A Diffusion of Innovation-Based Closeness Measure for Network Associations Permalink

Reihaneh Rabbany, Osmar R Zaiane 2011 IEEE 11th International Conference on Data Mining Workshops Paper ...

Web service matching for RESTful web services Permalink

Reihaneh Rabbany, Eleni Stroulia, Osmar R Zaiane Symposium on Web Systems Evolution Paper ...

Analyzing Participation of Students in Online Courses Using Social Network Analysis Techniques Permalink

Reihaneh Rabbany, M. Takaffoli, Osmar R Zaiane Educational Data Mining Paper Ab...

Meerkat: Community Mining with Dynamic Social Networks Permalink

Jiyang Chen, Justin Fagnan, R. Goebel, Reihaneh Rabbany, Farzad Sangi, M. Takaffoli, Eric Verbeek, Osmar R Zaiane 2010 IEEE International Conference on Data...

TGA

Static graph approximations of dynamic contact networks for epidemic forecasting Permalink

In this work, we introduce new, more rigorous evaluation procedures for link prediction in dynamic graphs, addressing the challenges and real-world considera...

Fast and Attributed Change Detection on Dynamic Graphs with Density of States Permalink

We introduce a novel spectral method called Scalable Change Point Detection (SCPD) to address the limitations of current solutions in detecting anomalous cha...

A Strong Node Classification Baseline for Temporal Graphs Permalink

Here we introduce a robust and effective baseline method for node classification in temporal graphs, serving as a benchmark for evaluating more complex model...

SigTran: Signature Vectors for Detecting Illicit Activities in Blockchain Transaction Networks Permalink

SigTran is an efficient graph-based method for identifying illicit nodes in blockchain networks. SigTran constructs a graph from blockchain transaction recor...

Incorporating dynamic flight network in SEIR to model mobility between populations Permalink

In this paper, we introduce a significant enhancement to the standard SEIR (Susceptible, Exposed, Infectious, Recovered) epidemiological model by integrating...

information-integrity

A Guide to Misinformation Detection Datasets Permalink

Data is a barrier to reliable misinformation detection solutions. To address this, we curated the largest collection of (mis)information datasets in the lite...

Web Retrieval Agents for Evidence-Based Misinformation Detection Permalink

We demonstrated an effective two LLM agent architecture for misinformation detection and fact-checking. It can increase the macro F1 of misinformation detect...

Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation Permalink

LLMs struggle with hallucinations and overconfident predictions. Uncertainty quantification can improve their reliability and helpfulness. We proposed an unc...

Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4 Permalink

We propose focusing on generalization, uncertainty, and how to leverage recent large language models, in order to create more practical tools to evaluate inf...

The Surprising Performance of Simple Baselines for Misinformation Detection Permalink

While many sophisticated detection models have been proposed in the literature, they were often compared with older NLP baselines such as SVMs, CNNs, and LST...

TGB

UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs Permalink

Here we introduce the Unified Temporal Graph (UTG) framework, which integrates snapshot-based and event-based machine learning models for temporal graphs und...

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs Permalink

TGB 2.0 introduces a novel benchmarking framework for evaluating methods for predicting future links on Temporal Knowledge Graphs (TKGs) and Temporal Heterog...

Temporal Graph Analysis with TGX Permalink

Here we introduce TGX, a Python package specifically designed for the analysis of temporal networks, addressing a gap in existing software libraries that pri...

Temporal Graph Benchmark for Machine Learning on Temporal Graphs Permalink

In this paper, we introduce the Temporal Graph Benchmark (TGB), a comprehensive collection of large-scale, diverse datasets designed for the realistic, repro...

Towards Better Evaluation for Dynamic Link Prediction Permalink

In this work, we introduce new, more rigorous evaluation procedures for link prediction in dynamic graphs, addressing the challenges and real-world considera...

online-crime

T-NET: Weakly Supervised Graph Learning for Combatting Human Trafficking Permalink

Detecting suspicious ads is challenging due to the sensitive, complex, and unlabeled nature of the data. T-Net addresses this as a weakly supervised graph le...

SWEET : Weakly Supervised Person Name Extraction for Fighting Human Trafficking Permalink

SWEET is a weak supervision pipeline for extracting person names from noisy escort ads, addressing the challenge of limited labeled data. SWEET combines rule...

TrafficVis: Visualizing Organized Activity and Spatio-Temporal Patterns for Detecting and Labeling Human Trafficking Permalink

TrafficVis is an interactive interface for detecting and labeling human trafficking (HT) in clusters of escort ads. Developed with domain experts, it uses ad...

INFOSHIELD: Generalizable Information-Theoretic Human-Trafficking Detection Permalink

INFOSHIELD is a scalable, parameter-free, and interpretable tool for detecting near-duplicate document clusters, with applications in human trafficking detec...

online-toxicity

Game On, Hate Off: A Study of Toxicity in Online Multiplayer Environments Permalink

While game companies are addressing the call to reduce toxicity and promote player health, the need to understand toxicity trends across time is important. W...

Towards Detecting Contextual Real-Time Toxicity for In-Game Chat Permalink

A simple and scalable model that reliably detects toxic content in real-time for a line of chat by including chat history and metadata. ToxBuster consistentl...

Unveiling Identity Biases in Toxicity Detection : A Game-Focused Dataset and Reactivity Analysis Approach Permalink

Identity biases arise commonly from annotated datasets, can be propagated in language models and can cause further harm to marginal groups. Existing bias ben...

ideology-and-polarization

Regional and Temporal Patterns of Partisan Polarization during the COVID-19 Pandemic in the United States and Canada Permalink

The COVID-19 pandemic sparked rigorous debate about public health measures online, as the timing and extent of interventions unfolded. This project evaluates...

An Evaluation of Language Models for Hyperpartisan Ideology Detection in Persian Twitter Permalink

While LLMs have demonstrated how effective they can be for tasks in the English language, such as detecting social media users’ political ideology, their per...

Party Prediction for Twitter Permalink

Partisanship has increasingly become a major point of contention in public discourse online, and as a result, researchers have developed a variety of methods...

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