Zobrazeno 1 - 10
of 8 230
pro vyhledávání: '"Jordan, W."'
Autor:
Xie, Qianqian, Li, Dong, Xiao, Mengxi, Jiang, Zihao, Xiang, Ruoyu, Zhang, Xiao, Chen, Zhengyu, He, Yueru, Han, Weiguang, Yang, Yuzhe, Chen, Shunian, Zhang, Yifei, Shen, Lihang, Kim, Daniel, Liu, Zhiwei, Luo, Zheheng, Yu, Yangyang, Cao, Yupeng, Deng, Zhiyang, Yao, Zhiyuan, Li, Haohang, Feng, Duanyu, Dai, Yongfu, Somasundaram, VijayaSai, Lu, Peng, Zhao, Yilun, Long, Yitao, Xiong, Guojun, Smith, Kaleb, Yu, Honghai, Lai, Yanzhao, Peng, Min, Nie, Jianyun, Suchow, Jordan W., Liu, Xiao-Yang, Wang, Benyou, Lopez-Lira, Alejandro, Huang, Jimin, Ananiadou, Sophia
Large language models (LLMs) have advanced financial applications, yet they often lack sufficient financial knowledge and struggle with tasks involving multi-modal inputs like tables and time series data. To address these limitations, we introduce \t
Externí odkaz:
http://arxiv.org/abs/2408.11878
Autor:
Yu, Yangyang, Yao, Zhiyuan, Li, Haohang, Deng, Zhiyang, Cao, Yupeng, Chen, Zhi, Suchow, Jordan W., Liu, Rong, Cui, Zhenyu, Zhang, Denghui, Subbalakshmi, Koduvayur, Xiong, Guojun, He, Yueru, Huang, Jimin, Li, Dong, Xie, Qianqian
Large language models (LLMs) have demonstrated notable potential in conducting complex tasks and are increasingly utilized in various financial applications. However, high-quality sequential financial investment decision-making remains challenging. T
Externí odkaz:
http://arxiv.org/abs/2407.06567
Autor:
Silber, Elizabeth A., Bowman, Daniel C., Carr, Chris G., Eisenberg, David P., Elbing, Brian R., Fernando, Benjamin, Garcés, Milton A., Haaser, Robert, Krishnamoorthy, Siddharth, Langston, Charles A., Nishikawa, Yasuhiro, Webster, Jeremy, Anderson, Jacob F., Arrowsmith, Stephen, Bazargan, Sonia, Beardslee, Luke, Beck, Brant, Bishop, Jordan W., Blom, Philip, Bracht, Grant, Chichester, David L., Christe, Anthony, Clarke, Jacob, Cummins, Kenneth, Cutts, James, Danielson, Lisa, Donahue, Carly, Eack, Kenneth, Fleigle, Michael, Fox, Douglas, Goel, Ashish, Green, David, Hasumi, Yuta, Hayward, Chris, Hicks, Dan, Hix, Jay, Horton, Stephen, Hough, Emalee, Huber, David P., Hunt, Madeline A., Inman, Jennifer, Islam, S. M. Ariful, Izraelevitz, Jacob, Jacob, Jamey D., Johnson, James, KC, Real J., Komjathy, Attila, Lam, Eric, LaPierre, Justin, Lewis, Kevin, Lewis, Richard D., Liu, Patrick, Martire, Léo, McCleary, Meaghan, McGhee, Elisa A., Mitra, Ipsita, Nag, Amitabh, Giraldo, Luis Ocampo, Pearson, Karen, Plaisir, Mathieu, Popenhagen, Sarah K., Rassoul, Hamid, Giannone, Miro Ronac, Samnani, Mirza, Schmerr, Nicholas, Spillman, Kate, Srinivas, Girish, Takazawa, Samuel K., Tempert, Alex, Turley, Reagan, Van Beek, Cory, Viens, Loïc, Walsh, Owen A., Weinstein, Nathan, White, Robert, Williams, Brian, Wilson, Trevor C., Wyckoff, Shirin, Yamamoto, Masa-yuki, Yap, Zachary, Yoshiyama, Tyler, Zeiler, Cleat
Sample Return Capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 24 September 2023 arrival of the OSIRIS-REx (Origins, Spectral Interpretation, Resource Id
Externí odkaz:
http://arxiv.org/abs/2407.02420
Autor:
Gurkan, Necdet, Suchow, Jordan W.
Publikováno v:
Proceedings of the 57th Hawaii International Conference on System Sciences, 713-723 (2024)
As the societal implications of Artificial Intelligence (AI) continue to grow, the pursuit of responsible AI necessitates public engagement in its development and governance processes. This involvement is crucial for capturing diverse perspectives an
Externí odkaz:
http://arxiv.org/abs/2402.00029
The rapid evolution of artificial intelligence (AI), especially in the domain of Large Language Models (LLMs) and generative AI, has opened new avenues for application across various fields, yet its role in business education remains underexplored. T
Externí odkaz:
http://arxiv.org/abs/2401.02985
Autor:
Yu, Yangyang, Li, Haohang, Chen, Zhi, Jiang, Yuechen, Li, Yang, Zhang, Denghui, Liu, Rong, Suchow, Jordan W., Khashanah, Khaldoun
Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in question-answering (QA) tasks across diverse domains. Their prowess in integrating extensive web knowledge has fueled interest in developing LLM-based autonomous a
Externí odkaz:
http://arxiv.org/abs/2311.13743
Autor:
Gürkan, Necdet, Suchow, Jordan W.
Harnessing collective intelligence to drive effective decision-making and collaboration benefits from the ability to detect and characterize heterogeneity in consensus beliefs. This is particularly true in domains such as technology acceptance or lea
Externí odkaz:
http://arxiv.org/abs/2309.09787
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-19 (2024)
Abstract Differential accessibility (DA) analysis of single-cell epigenomics data enables the discovery of regulatory programs that establish cell type identity and steer responses to physiological and pathophysiological perturbations. While many sta
Externí odkaz:
https://doaj.org/article/793d4834872a4dac9d9bba82d4a07595
Autor:
Yu, Yangyang, Suchow, Jordan W.
High-dimensional deep neural network representations of images and concepts can be aligned to predict human annotations of diverse stimuli. However, such alignment requires the costly collection of behavioral responses, such that, in practice, the de
Externí odkaz:
http://arxiv.org/abs/2306.05331