Zobrazeno 1 - 10
of 30 179
pro vyhledávání: '"Tse P"'
Autor:
Wang, Wenxuan, Shi, Juluan, Wang, Chaozheng, Lee, Cheryl, Yuan, Youliang, Huang, Jen-tse, Lyu, Michael R.
Equipped with the capability to call functions, modern large language models (LLMs) can leverage external tools for addressing a range of tasks unattainable through language skills alone. However, the effective execution of these tools relies heavily
Externí odkaz:
http://arxiv.org/abs/2409.00557
Relative free energy calculations are now widely used in academia and industry, but the accuracy is often limited by poor sampling of the complexes conformational ensemble. To address this, we have developed a novel method termed Multi-Topology Repli
Externí odkaz:
http://arxiv.org/abs/2408.11038
Autor:
Hao, Xianglin, Yin, Ke, Cai, Shiqing, Zou, Jianlong, Wang, Ruibin, Ma, Xikui, Tse, Chi K., Dong, Tianyu
Parity-time symmetry is a fundamental concept in non-Hermitian physics that has recently gained attention for its potential in engineering advanced electronic systems and achieving robust wireless power transfer even in the presence of disturbances,
Externí odkaz:
http://arxiv.org/abs/2408.06913
Autor:
Dong, Xinshu, Litos, Orfeas Stefanos Thyfronitis, Tas, Ertem Nusret, Tse, David, Woll, Robin Linus, Yang, Lei, Yu, Mingchao
Proof-of-stake (PoS) blockchains require validators to lock their tokens as collateral, slashing these tokens if they are identified as protocol violators. PoS chains have mostly been secured by their native tokens. However, using only the native tok
Externí odkaz:
http://arxiv.org/abs/2408.01896
Log parsing is a critical step that transforms unstructured log data into structured formats, facilitating subsequent log-based analysis. Traditional syntax-based log parsers are efficient and effective, but they often experience decreased accuracy w
Externí odkaz:
http://arxiv.org/abs/2408.01585
Autor:
Huang, Jen-tse, Zhou, Jiaxu, Jin, Tailin, Zhou, Xuhui, Chen, Zixi, Wang, Wenxuan, Yuan, Youliang, Sap, Maarten, Lyu, Michael R.
Multi-agent systems, powered by large language models, have shown great abilities across various tasks due to the collaboration of expert agents, each focusing on a specific domain. However, when agents are deployed separately, there is a risk that m
Externí odkaz:
http://arxiv.org/abs/2408.00989
Autor:
Yuan, Youliang, Jiao, Wenxiang, Wang, Wenxuan, Huang, Jen-tse, Xu, Jiahao, Liang, Tian, He, Pinjia, Tu, Zhaopeng
This study addresses a critical gap in safety tuning practices for Large Language Models (LLMs) by identifying and tackling a refusal position bias within safety tuning data, which compromises the models' ability to appropriately refuse generating un
Externí odkaz:
http://arxiv.org/abs/2407.09121
Lomics: Generation of Pathways and Gene Sets using Large Language Models for Transcriptomic Analysis
Autor:
Wong, Chun-Ka, Choo, Ali, Cheng, Eugene C. C., San, Wing-Chun, Cheng, Kelvin Chak-Kong, Lau, Yee-Man, Lin, Minqing, Li, Fei, Liang, Wei-Hao, Liao, Song-Yan, Ng, Kwong-Man, Hung, Ivan Fan-Ngai, Tse, Hung-Fat, Wong, Jason Wing-Hon
Interrogation of biological pathways is an integral part of omics data analysis. Large language models (LLMs) enable the generation of custom pathways and gene sets tailored to specific scientific questions. These targeted sets are significantly smal
Externí odkaz:
http://arxiv.org/abs/2407.09089
Children often suffer wrist injuries in daily life, while fracture injuring radiologists usually need to analyze and interpret X-ray images before surgical treatment by surgeons. The development of deep learning has enabled neural network models to w
Externí odkaz:
http://arxiv.org/abs/2407.03163
The role-play ability of Large Language Models (LLMs) has emerged as a popular research direction. However, existing studies focus on imitating well-known public figures or fictional characters, overlooking the potential for simulating ordinary indiv
Externí odkaz:
http://arxiv.org/abs/2404.13957