Zhijing Jin
About
Appointed Canada CIFAR AI Chair – 2025
Zhijing Jin is a Canada CIFAR AI Chair at the Vector Institute and an assistant professor at the University of Toronto. Her research areas are large language models (LLMs), natural language processing (NLP), and causal inference. She is highly interested in how causal influence can help people’s daily lives by sharpening the ability to recognize truth and falsehood in news articles, help scientists draw right conclusions from data and existing theories and help policymakers decide interventions that can make society better. Her research also revolves around multi-agent LLM simulations, drawing insights on AI behavioral tendencies (e.g., GovSim, SanctSim and MoralSim).
Awards
- Honorable mention, Wilhelm Schickard Dissertation Award (2025)
- Best Paper Award, NeurIPS 2024 Workshop on Pluralistic Alignment (2024)
- Best Paper Award, NeurIPS 2024 Workshop on Causality and Language Models (2024)
- Postdoctoral Fellowship by the Future of Life Institute (2024-2025)
- EECS Rising Star (2023)
Relevant Publications
- Jin, Z., Chen, Y., Leeb, F., Gresele, L., Kamal, O., Lyu, Z., Blin, K., Gonzalez Adauto, F., Kleiman-Weiner, M., Sachan, M., & Schölkopf, B. (2023). “CLadder: Assessing Causal Reasoning in Language Models.” Thirty-seventh Conference on Neural Information Processing Systems NeurIPS)
- Jin, Z., Liu, J., Lyu, Z., Poff, S., Sachan, M., Mihalcea, R., Diab, M., & Schölkopf, B. (2024). “Can Large Language Models Infer Causation from Correlation?” International Conference on Learning Representations (ICLR).
- Jin, D., Jin, Z., Zhou, J. T., & Szolovits, P. (2020). “Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment.” Proceedings of the AAAI Conference on Artificial Intelligence, 34(05), pp. 8018–8025.
- Stolfo, A., Jin, Z., Shridhar, K., Schölkopf, B., & Sachan, M. (2023). “A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models.” Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL).
- Piatti, G., Jin, Z., Kleiman-Weiner, M., Schölkopf, B., Sachan, M., & Mihalcea, R. (2024). “Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents.” Thirty-eighth Conference on Neural Information Processing Systems (NeurIPS).