Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Li, Haohang"'
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:
Xie, Qianqian, Han, Weiguang, Chen, Zhengyu, Xiang, Ruoyu, Zhang, Xiao, He, Yueru, Xiao, Mengxi, Li, Dong, Dai, Yongfu, Feng, Duanyu, Xu, Yijing, Kang, Haoqiang, Kuang, Ziyan, Yuan, Chenhan, Yang, Kailai, Luo, Zheheng, Zhang, Tianlin, Liu, Zhiwei, Xiong, Guojun, Deng, Zhiyang, Jiang, Yuechen, Yao, Zhiyuan, Li, Haohang, Yu, Yangyang, Hu, Gang, Huang, Jiajia, Liu, Xiao-Yang, Lopez-Lira, Alejandro, Wang, Benyou, Lai, Yanzhao, Wang, Hao, Peng, Min, Ananiadou, Sophia, Huang, Jimin
LLMs have transformed NLP and shown promise in various fields, yet their potential in finance is underexplored due to a lack of comprehensive evaluation benchmarks, the rapid development of LLMs, and the complexity of financial tasks. In this paper,
Externí odkaz:
http://arxiv.org/abs/2402.12659
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
Large Language Models (LLMs), prominently highlighted by the recent evolution in the Generative Pre-trained Transformers (GPT) series, have displayed significant prowess across various domains, such as aiding in healthcare diagnostics and curating an
Externí odkaz:
http://arxiv.org/abs/2309.03736
Autor:
Xiao, Jinjie, Li, Haohang, Liu, Zhicheng, Cui, Ruoheng, Luo, Fuyong, Chen, Junsheng, Shen, Jian, Li, Chaoyang
Publikováno v:
In Optics Communications 15 November 2024 571
Autor:
Yang, Ying, Kong, Xiangguang, Li, Haohang, Shang, Chunli, Zhang, Haonan, Zhou, Biao, Ren, Yang, Hao, Shijie
Publikováno v:
In Materials Chemistry and Physics 15 October 2023 308
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