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Experimental Sensing Quantum Atmosphere of a Single Spin

Published in Quantum Frontier, 2020

With Zhiping Yang, Zhijie Li, Qing-Dong Jiang, Zihua Chai, Changkui Duan, Ya Wang, Xing Rong and Jiangfeng Du.

Recommended citation: Zhu, Kehang, et al. "Experimental sensing quantum atmosphere of a single spin." Quantum Frontiers 3.1 (2024): 1. https://link.springer.com/article/10.1007/s44214-023-00048-8

Dynamics of a tunable QED in quantum spin ice

Published in APS March Meeting, 2021

With Siddhardh Morampudi, Yeqi Huang, Youjin Deng and Frank Wilczek. Accepted at APS March Meeting 2022 as focused talk.

Recommended citation: Kehang Zhu, et.al. (2021). Dynamics of a tunable QED in quantum spin ice.

Reading Between the Pixels: Investigating the Conceptual Hurdles to Visualization Literacy

Published in Accepted in IEEE CHI 2024, 2023

With Carolina Nobre, Eric Morth, Hanspeter Pfister and Johanna Beyer.

Recommended citation: Carolina Nobre, Kehang Zhu, et.al. (2023). Reading Between the Pixels: Investigating the Conceptuxal Hurdles to Visualization Literacy

Silica Scientist: A Tool for Automated Causal Hypothesis Generation and Simulated Experimental Validation

Published in CODE, 2023

With Benjamin Manning and John Horton

Recommended citation: Kehang Zhu*, Benjamin Manning*, John Horton. Silica Scientist: A Tool for Automated Causal Hypothesis Generation and Simulated Experimental Validation (2023 CODE)

Automated Social Science: Using Large language Models to Identify Causal Relationships in Social Phenomena

Published in ICLC, 2023

With Benjamin Manning and John Horton

Recommended citation: Benjamin Manning*, Kehang Zhu*, John Horton. Automated Social Science: Using Large language Models to Identify Causal Relationships in Social Phenomena (2023 ICLC)

ComplexityNet: Increasing LLM Inference Efficiency by Learning Task Complexity

Published in Arxiv, 2023

With Henry Bae, Aghyad Deeb and Alex Fleury.

Recommended citation: Bae, Henry, Aghyad Deeb, Alex Fleury, and Kehang Zhu. "ComplexityNet: Increasing LLM Inference Efficiency by Learning Task Complexity." arXiv preprint arXiv:2312.11511 (2023). https://arxiv.org/abs/2312.11511

Automated Social Science: Language Models as Scientist and Subjects

Published in NBER working paper, 2024

Paper

Recommended citation: Manning, Benjamin S., Kehang Zhu, and John J. Horton. Automated Social Science: Language Models as Scientist and Subjects. No. w32381. National Bureau of Economic Research, 2024.