Zobrazeno 1 - 10
of 1 041
pro vyhledávání: '"Yao, Zhiyuan"'
Autor:
Yao, Zhiyuan, Zhang, Pengfei
Quantum many-body scars (QMBS) -- rare eigenstates that evade thermalization -- are typically characterized by their low entanglement entropies compared to surrounding thermal eigenstates. However, due to finite-size effects in systems accessible via
Externí odkaz:
http://arxiv.org/abs/2410.21812
Theory and observations reveal that the circumgalactic medium (CGM) and the cosmic web at high redshifts are multiphase, with small clouds of cold gas embedded in a hot, diffuse medium. A proposed mechanism is `shattering' of large, thermally unstabl
Externí odkaz:
http://arxiv.org/abs/2410.12914
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, Xu, Zhaozhuo, 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
The integration of Large Language Models (LLMs) into financial analysis has garnered significant attention in the NLP community. This paper presents our solution to IJCAI-2024 FinLLM challenge, investigating the capabilities of LLMs within three crit
Externí odkaz:
http://arxiv.org/abs/2407.01953
Investors and regulators can greatly benefit from a realistic market simulator that enables them to anticipate the consequences of their decisions in real markets. However, traditional rule-based market simulators often fall short in accurately captu
Externí odkaz:
http://arxiv.org/abs/2403.19781
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
Anomaly detection plays a crucial role in ensuring network robustness. However, implementing intelligent alerting systems becomes a challenge when considering scenarios in which anomalies can be caused by both malicious and non-malicious events, lead
Externí odkaz:
http://arxiv.org/abs/2402.10085
In this paper we are introducing a new reinforcement learning method for control problems in environments with delayed feedback. Specifically, our method employs stochastic planning, versus previous methods that used deterministic planning. This allo
Externí odkaz:
http://arxiv.org/abs/2402.00313
Anomaly detection is an important task in network management. However, deploying intelligent alert systems in real-world large-scale networking systems is challenging when we take into account (i) scalability, (ii) data heterogeneity, and (iii) gener
Externí odkaz:
http://arxiv.org/abs/2306.07983