Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Qin, Lianhui"'
Autor:
Guo, Xingang, Keivan, Darioush, Syed, Usman, Qin, Lianhui, Zhang, Huan, Dullerud, Geir, Seiler, Peter, Hu, Bin
Control system design is a crucial aspect of modern engineering with far-reaching applications across diverse sectors including aerospace, automotive systems, power grids, and robotics. Despite advances made by Large Language Models (LLMs) in various
Externí odkaz:
http://arxiv.org/abs/2410.19811
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, GPT-4o, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, Llama 3, and Llama 3.1 in solving some selected undergraduate-level transportation en
Externí odkaz:
http://arxiv.org/abs/2408.08302
Autor:
Ma, Chengqian, Hua, Zhanxiang, Anderson-Frey, Alexandra, Iyer, Vikram, Liu, Xin, Qin, Lianhui
Severe convective weather events, such as hail, tornadoes, and thunderstorms, often occur quickly yet cause significant damage, costing billions of dollars every year. This highlights the importance of forecasting severe weather threats hours in adva
Externí odkaz:
http://arxiv.org/abs/2406.11217
The ability to generate diverse solutions to a given problem is a hallmark of human creativity. This divergent reasoning is also crucial for machines, enhancing their robustness and enabling them to assist humans in many applications such as scientif
Externí odkaz:
http://arxiv.org/abs/2406.05673
Autor:
Kevian, Darioush, Syed, Usman, Guo, Xingang, Havens, Aaron, Dullerud, Geir, Seiler, Peter, Qin, Lianhui, Hu, Bin
In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra in solving undergraduate-level control problems. Controls provides an interesting case study for LLM reason
Externí odkaz:
http://arxiv.org/abs/2404.03647
Student simulation in online education is important to address dynamic learning behaviors of students with diverse backgrounds. Existing simulation models based on deep learning usually need massive training data, lacking prior knowledge in education
Externí odkaz:
http://arxiv.org/abs/2404.07963
Electronic health records (EHRs) contain valuable patient data for health-related prediction tasks, such as disease prediction. Traditional approaches rely on supervised learning methods that require large labeled datasets, which can be expensive and
Externí odkaz:
http://arxiv.org/abs/2403.15464
Jailbreaks on large language models (LLMs) have recently received increasing attention. For a comprehensive assessment of LLM safety, it is essential to consider jailbreaks with diverse attributes, such as contextual coherence and sentiment/stylistic
Externí odkaz:
http://arxiv.org/abs/2402.08679
Autor:
Englhardt, Zachary, Ma, Chengqian, Morris, Margaret E., Xu, Xuhai "Orson", Chang, Chun-Cheng, Qin, Lianhui, McDuff, Daniel, Liu, Xin, Patel, Shwetak, Iyer, Vikram
Publikováno v:
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 8, Issue 2, May 2024
Passively collected behavioral health data from ubiquitous sensors holds significant promise to provide mental health professionals insights from patient's daily lives; however, developing analysis tools to use this data in clinical practice requires
Externí odkaz:
http://arxiv.org/abs/2311.13063
Autor:
Tian, Yufei, Ravichander, Abhilasha, Qin, Lianhui, Bras, Ronan Le, Marjieh, Raja, Peng, Nanyun, Choi, Yejin, Griffiths, Thomas L., Brahman, Faeze
We explore the creative problem-solving capabilities of modern LLMs in a novel constrained setting. To this end, we create MACGYVER, an automatically generated dataset consisting of over 1,600 real-world problems deliberately designed to trigger inno
Externí odkaz:
http://arxiv.org/abs/2311.09682