Portrait de Sneheel Sarangi

Sneheel Sarangi

Collaborateur·rice de recherche - McGill
Superviseur⋅e principal⋅e
Sujets de recherche
Alignement de l'IA
Apprentissage multimodal
Apprentissage par renforcement
Apprentissage profond
Généralisation hors distribution (OOD)
Grands modèles de langage (LLM)
IA responsable
Modèles génératifs
Raisonnement
Traitement du langage naturel

Publications

SandboxSocial: A Sandbox for Social Media Using Multimodal AI Agents
Gayatri Krishnakumar
Busra Tugce Gurbuz
Austin Welch
Hao Yu
Ethan Kosak-Hine
Tom Gibbs
Dan Zhao
SandboxSocial: A Sandbox for Social Media Using Multimodal AI Agents
Gayatri K
Busra Tugce Gurbuz
Austin Welch
Hao Yu
Ethan Kosak-Hine
Tom Gibbs
Dan Zhao
The online information ecosystem enables influence campaigns of unprecedented scale and impact. We urgently need empirically grounded approa… (voir plus)ches to counter the growing threat of malicious campaigns, now amplified by generative AI. But, developing defenses in real-world settings is impractical. Social system simulations with agents modelled using Large Language Models (LLMs) are a promising alternative approach and a growing area of research. However, existing simulators lack features needed to capture the complex information-sharing dynamics of platform-based social networks. To bridge this gap, we present SandboxSocial, a new simulator that includes several key innovations, mainly: (1) a virtual social media platform (modelled as Mastodon and mirrored in an actual Mastodon server) that enables a realistic setting in which agents interact; (2) an adapter that uses real-world user data to create more grounded agents and social media content; and (3) multi-modal capabilities that enable our agents to interact using both text and images---just as humans do on social media. We make the simulator more useful to researchers by providing measurement and analysis tools that track simulation dynamics and compute evaluation metrics to compare experimental results.
A Simulation System Towards Solving Societal-Scale Manipulation
Austin Welch
Gayatri Krishnakumar
Dan Zhao
Hao Yu
Ethan Kosak-Hine
Tom Gibbs
Busra Tugce Gurbuz
The rise of AI-driven manipulation poses significant risks to societal trust and democratic processes. Yet, studying these effects in real-w… (voir plus)orld settings at scale is ethically and logistically impractical, highlighting a need for simulation tools that can model these dynamics in controlled settings to enable experimentation with possible defenses. We present a simulation environment designed to address this. We elaborate upon the Concordia framework that simulates offline, `real life' activity by adding online interactions to the simulation through social media with the integration of a Mastodon server. We improve simulation efficiency and information flow, and add a set of measurement tools, particularly longitudinal surveys. We demonstrate the simulator with a tailored example in which we track agents' political positions and show how partisan manipulation of agents can affect election results.
A Simulation System Towards Solving Societal-Scale Manipulation
Austin Welch
Gayatri K
Dan Zhao
Hao Yu
Ethan Kosak-Hine
Tom Gibbs
Busra Tugce Gurbuz
The rise of AI-driven manipulation poses significant risks to societal trust and democratic processes. Yet, studying these effects in real-w… (voir plus)orld settings at scale is ethically and logistically impractical, highlighting a need for simulation tools that can model these dynamics in controlled settings to enable experimentation with possible defenses. We present a simulation environment designed to address this. We elaborate upon the Concordia framework that simulates offline, `real life' activity by adding online interactions to the simulation through social media with the integration of a Mastodon server. We improve simulation efficiency and information flow, and add a set of measurement tools, particularly longitudinal surveys. We demonstrate the simulator with a tailored example in which we track agents' political positions and show how partisan manipulation of agents can affect election results.
Simulation System Towards Solving Societal-Scale Manipulation
Austin Welch
Gayatri K
Dan Zhao
Hao Yu
Tom Gibbs
Ethan Kosak-Hine
Busra Tugce Gurbuz
The rise of AI-driven manipulation poses significant risks to societal trust and democratic processes. Yet, studying these effects in real-w… (voir plus)orld settings at scale is ethically and logistically impractical, highlighting a need for simulation tools that can model these dynamics in controlled settings to enable experimentation with possible defenses. We present a simulation environment designed to address this. We elaborate upon the Concordia framework that simulates offline, `real life' activity by adding online interactions to the simulation through social media with the integration of a Mastodon server. Through a variety of means we then improve simulation efficiency and information flow, and add a set of measurement tools, particularly longitudinal surveys of the agents' political positions. We demonstrate the simulator with a tailored example of how partisan manipulation of agents can affect election results.
Simulation System Towards Solving Societal-Scale Manipulation
Austin Welch
Gayatri K
Dan Zhao
Hao Yu
Tom Gibbs
Ethan Kosak-Hine
Busra Tugce Gurbuz
The rise of AI-driven manipulation poses significant risks to societal trust and democratic processes. Yet, studying these effects in real-w… (voir plus)orld settings at scale is ethically and logistically impractical, highlighting a need for simulation tools that can model these dynamics in controlled settings to enable experimentation with possible defenses. We present a simulation environment designed to address this. We elaborate upon the Concordia framework that simulates offline, `real life' activity by adding online interactions to the simulation through social media with the integration of a Mastodon server. Through a variety of means we then improve simulation efficiency and information flow, and add a set of measurement tools, particularly longitudinal surveys of the agents' political positions. We demonstrate the simulator with a tailored example of how partisan manipulation of agents can affect election results.