The Computational Social Science Lab is an interdisciplinary research group that works at the intersection of AI, data, and society. We are part of the Department of Computer Science at the University of Toronto.

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Selected Research

Maia-2: A Unified Model for Human-AI Alignment in Chess
Zhenwei Tang, Difan Jiao, Reid McIlroy-Young, Jon Kleinberg, Siddhartha Sen, and Ashton Anderson. NeurIPS.
SPIN: Sparsifying and Integrating Internal Neurons in Large Language Models for Text Classification
Difan Jiao, Yilun Liu, Zhenwei Tang, Daniel Matter, Jürgen Pfeffer, and Ashton Anderson. ACL Findings 2024.
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
Karim Hamade, Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg, and Ashton Anderson. ICLR 2024.
ICL-Markup: Structuring In-Context Learning using Soft-Token Tags
Marc-Etienne Brunet, Ashton Anderson, and Rich Zemel. NeurIPS R0-FoMo Workshop 2023.
Echo Tunnels: Polarized News Sharing Online Runs Narrow but Deep
Lillio Mok, Michael Inzlicht, and Ashton Anderson. ICWSM 2023.
Reddit in the Time of COVID
Venia Veselovsky and Ashton Anderson. ICWSM 2023.
Implications of Model Indeterminacy for Explanations of Automated Decisions
Marc-Etienne Brunet, Ashton Anderson, and Rich Zemel. NeurIPS 2022.
Mimetic Models: Ethical Implications of AI that Acts Like You
Reid McIlroy-Young, Russell Wang, Siddhartha Sen, Jon Kleinberg, and Ashton Anderson. AIES 2022.
Learning Models of Individual Behavior in Chess
Reid McIlroy-Young, Russell Wang, Siddhartha Sen, Jon Kleinberg, and Ashton Anderson. KDD 2022.
Quantifying the Creator Economy: A Large-Scale Analysis of Patreon
Lana El Sanyoura and Ashton Anderson. ICWSM 2022.
All publications