2 citations · 10 across the 32 of their papers we have counts for
33 papers
StabilityBench: Benchmarking Instability in LLMs
Emma Kondrup, Zachary Yang, Anne Imouza +1
AI Assistants are increasingly deployed in high-stakes settings, such as healthcare or government services. Yet their real-world behavior remains poorly understood due to strong co…
EASE Configuration Facilitates A Reproducible Science of LLM Social Simulations
Sneheel Sarangi, Maximilian Puelma Touzel, Aurélien Bück-Kaeffer +3
LLMs are increasingly deployed to simulate social interactions, yet many of the existing simulators remain ad hoc and monolithic. This lack of architectural standardization prevent…
Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection
Victor Livernoche, Jie Zan, Reihaneh Rabbany
Denoising score matching (DSM) provides a way to learn data distributions by training a neural network to recover the score function, defined as the gradient of the log density, fr…
ControBench: An Interaction-Aware Benchmark for Controversial Discourse Analysis on Social Networks
Ta Thanh Thuy, Jiaqi Zhu, Xuan Liu +6
Understanding how people argue across ideological divides online is important for studying political polarization, misinformation, and content moderation. Existing datasets capture…
The Cookbook: Design Space of LLM-based Social Simulations
Aurélien Bück-Kaeffer, Sneheel Sarangi, Maximilian Puelma Touzel +3
Studies attempting to simulate human behavior with grow in numbers while LLM-only social networks have started appearing outside of controlled settings…
What do people want to fact-check?
Bijean Ghafouri, Dorsaf Sallami, Luca Luceri +4
Research on misinformation has focused almost exclusively on supply, asking what falsehoods circulate, who produces them, and whether corrections work. A basic demand-side question…
Deepfakes in the 2025 Canadian Election: Prevalence, Partisanship, and Platform Dynamics
Victor Livernoche, Andreea Musulan, Zachary Yang +2
Concerns about AI-generated political content are growing, yet there is limited empirical evidence on how deepfakes actually appear and circulate across social platforms during maj…
TGM: a Modular and Efficient Library for Machine Learning on Temporal Graphs
Jacob Chmura, Shenyang Huang, Tran Gia Bao Ngo +7
Well-designed open-source software drives progress in Machine Learning (ML) research. While static graph ML enjoys mature frameworks like PyTorch Geometric and DGL, ML for temporal…
OpenFake: An Open Dataset and Platform Toward Real-World Deepfake Detection
Victor Livernoche, Akshatha Arodi, Andreea Musulan +5
Deepfakes, synthetic media created using advanced AI techniques, pose a growing threat to information integrity, particularly in politically sensitive contexts. This challenge is a…
: A Social Media User Dataset for LLM Persona Evaluation and Training
Aurélien Bück-Kaeffer, Je Qin Chooi, Dan Zhao +5
Large language models (LLMs) offer promising capabilities for simulating social media dynamics at scale, enabling studies that would be ethically or logistically challenging with h…
CrediBench: Building Web-Scale Network Datasets for Information Integrity
Emma Kondrup, Sebastian Sabry, Hussein Abdallah +9
Automatically assessing the credibility of online sources presents an invaluable tool for navigating today's information ecosystem. However, existing approaches either depend on sc…
RL Fine-Tuning Heals OOD Forgetting in SFT
Hangzhan Jin, Sitao Luan, Tianwei Ni +5
Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) is a standard post-training recipe for improving Large Language Models (LLM) reasoning, but why it works remain…
The Singapore Consensus on Global AI Safety Research Priorities
Yoshua Bengio, Tegan Maharaj, Luke Ong +84
Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i.e., trustworthy,…
Ask before you Build: Rethinking AI-for-Good in Human Trafficking Interventions
Pratheeksha Nair, Gabriel Lefebvre, Sophia Garrel +2
AI for good initiatives often rely on the assumption that technical interventions can resolve complex social problems. In the context of human trafficking (HT), such techno-solutio…
Veracity: An Open-Source AI Fact-Checking System
Taylor Lynn Curtis, Maximilian Puelma Touzel, William Garneau +8
The proliferation of misinformation poses a significant threat to society, exacerbated by the capabilities of generative AI. This demo paper introduces Veracity, an open-source AI…
Are Large Language Models Good Temporal Graph Learners?
Shenyang Huang, Ali Parviz, Emma Kondrup +5
Large Language Models (LLMs) have recently driven significant advancements in Natural Language Processing and various other applications. While a broad range of literature has expl…
Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection
Zachary Yang, Domenico Tullo, Reihaneh Rabbany
Toxicity detection in gaming communities faces significant scaling challenges when expanding across multiple games and languages, particularly in real-time environments where compu…
The Structural Safety Generalization Problem
Julius Broomfield, Tom Gibbs, Ethan Kosak-Hine +7
LLM jailbreaks are a widespread safety challenge. Given this problem has not yet been tractable, we suggest targeting a key failure mechanism: the failure of safety to generalize a…
From Intuition to Understanding: Using AI Peers to Overcome Physics Misconceptions
Ruben Weijers, Denton Wu, Hannah Betts +10
Generative AI has the potential to transform personalization and accessibility of education. However, it raises serious concerns about accuracy and helping students become independ…
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy
Khaoula Chehbouni, Martine De Cock, Gilles Caporossi +3
The increased screen time and isolation caused by the COVID-19 pandemic have led to a significant surge in cases of online grooming, which is the use of strategies by predators to…
Online Influence Campaigns: Strategies and Vulnerabilities
Andreea Musulan, Veronica Xia, Ethan Kosak-Hine +5
In order to combat the creation and spread of harmful content online, this paper defines and contextualizes the concept of inauthentic, societal-scale manipulation by malicious act…
Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data
Soroush Omranpour, Guillaume Rabusseau, Reihaneh Rabbany
In this paper, we tackle the challenge of predicting stock movements in financial markets by introducing Higher Order Transformers, a novel architecture designed for processing mul…
Higher-Order Transformers With Kronecker-Structured Attention
Soroush Omranpour, Guillaume Rabusseau, Reihaneh Rabbany
Modern datasets are increasingly high-dimensional and multiway, often represented as tensor-valued data with multi-indexed variables. While Transformers excel in sequence modeling…
Epistemic Integrity in Large Language Models
Bijean Ghafouri, Shahrad Mohammadzadeh, James Zhou +8
Large language models are increasingly relied upon as sources of information, but their propensity for generating false or misleading statements with high confidence poses risks fo…