Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Li, Siyuan"'
Unmanned Combat Aerial Vehicle (UCAV) dogfight, which refers to a fight between two or more UCAVs usually at close quarters, plays a decisive role on the aerial battlefields. With the evolution of artificial intelligence, dogfight progressively trans
Externí odkaz:
http://arxiv.org/abs/2406.11562
Autor:
Lin, Haitao, Zhao, Guojiang, Zhang, Odin, Huang, Yufei, Wu, Lirong, Liu, Zicheng, Li, Siyuan, Tan, Cheng, Gao, Zhifeng, Li, Stan Z.
Structure-based drug design (SBDD) aims to generate potential drugs that can bind to a target protein and is greatly expedited by the aid of AI techniques in generative models. However, a lack of systematic understanding persists due to the diverse s
Externí odkaz:
http://arxiv.org/abs/2406.10840
To mitigate the computational complexity in the self-attention mechanism on long sequences, linear attention utilizes computation tricks to achieve linear complexity, while state space models (SSMs) popularize a favorable practice of using non-data-d
Externí odkaz:
http://arxiv.org/abs/2406.08128
Autor:
Tan, Cheng, Lyu, Dongxin, Li, Siyuan, Gao, Zhangyang, Wei, Jingxuan, Ma, Siqi, Liu, Zicheng, Li, Stan Z.
Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields and have shown significant potential in the academic peer-review process. However, existing applications are primarily limited to static review generation
Externí odkaz:
http://arxiv.org/abs/2406.05688
Autor:
Liu, Zicheng, Li, Jiahui, Li, Siyuan, Zang, Zelin, Tan, Cheng, Huang, Yufei, Bai, Yajing, Li, Stan Z.
The Genomic Foundation Model (GFM) paradigm is expected to facilitate the extraction of generalizable representations from massive genomic data, thereby enabling their application across a spectrum of downstream applications. Despite advancements, a
Externí odkaz:
http://arxiv.org/abs/2406.01627
Autor:
Gan, Chunjing, Yang, Dan, Hu, Binbin, Zhang, Hanxiao, Li, Siyuan, Liu, Ziqi, Shen, Yue, Ju, Lin, Zhang, Zhiqiang, Gu, Jinjie, Liang, Lei, Zhou, Jun
In recent years, large language models (LLMs) have made remarkable achievements in various domains. However, the untimeliness and cost of knowledge updates coupled with hallucination issues of LLMs have curtailed their applications in knowledge inten
Externí odkaz:
http://arxiv.org/abs/2405.19893
Autor:
Gao, Zhangyang, Wang, Jue, Tan, Cheng, Wu, Lirong, Huang, Yufei, Li, Siyuan, Ye, Zhirui, Li, Stan Z.
Molecule inverse folding has been a long-standing challenge in chemistry and biology, with the potential to revolutionize drug discovery and material science. Despite specified models have been proposed for different small- or macro-molecules, few ha
Externí odkaz:
http://arxiv.org/abs/2405.18968
Autor:
Wu, Lirong, Tian, Yijun, Lin, Haitao, Huang, Yufei, Li, Siyuan, Chawla, Nitesh V, Li, Stan Z.
Protein-protein bindings play a key role in a variety of fundamental biological processes, and thus predicting the effects of amino acid mutations on protein-protein binding is crucial. To tackle the scarcity of annotated mutation data, pre-training
Externí odkaz:
http://arxiv.org/abs/2405.10348
Transformer models have been successful in various sequence processing tasks, but the self-attention mechanism's computational cost limits its practicality for long sequences. Although there are existing attention variants that improve computational
Externí odkaz:
http://arxiv.org/abs/2404.11163
Offline batch inference is a common task in the industry for deep learning applications, but it can be challenging to ensure stability and performance when dealing with large amounts of data and complicated inference pipelines. This paper demonstrate
Externí odkaz:
http://arxiv.org/abs/2404.09686