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Can LLMs Achieve Casual Reasoning and Cooperation?
Abstract
Zhijing Jin (she/her) is an incoming assistant professor at the University of Toronto. Her PhD is at Max Planck Institute & ETH. She works on socially responsible NLP by causal inference. Specifically, her research focuses on causal reasoning with LLMs, causal methods to improve robustness, interpretability, and fairness of LLMs, as well as causal analysis of social problems. She has received 3 Rising Star awards, 2 PhD Fellowships. Her work has published at many NLP and AI venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR, AAAI), and featured in MIT News and ACM TechNews. She co-organizes many workshops (e.g., NLP for Positive Impact Workshop at EMNLP 2024, and Moral AI Workshop at NeurIPS 2023), and leads the Tutorial on Causality for LLMs at NeurIPS 2024, and Tutorial on CausalNLP at EMNLP 2022.
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