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Autor:
Sun, Hao, Wu, Jiayi, Cai, Hengyi, Wei, Xiaochi, Feng, Yue, Wang, Bo, Wang, Shuaiqiang, Zhang, Yan, Yin, Dawei
Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality and deploying local-based LLMs for lower computational cost. The former option is typically costly and
Externí odkaz:
http://arxiv.org/abs/2410.13181
Despite advancements in enhancing LLM safety against jailbreak attacks, evaluating LLM defenses remains a challenge, with current methods often lacking explainability and generalization to complex scenarios, leading to incomplete assessments (e.g., d
Externí odkaz:
http://arxiv.org/abs/2410.12855
Autor:
Shi, Zhengliang, Gao, Shen, Chen, Xiuyi, Feng, Yue, Yan, Lingyong, Shi, Haibo, Yin, Dawei, Chen, Zhumin, Verberne, Suzan, Ren, Zhaochun
Augmenting large language models (LLMs) with external tools has emerged as a promising approach to extend their utility, empowering them to solve practical tasks. Existing work typically empowers LLMs as tool users with a manually designed workflow,
Externí odkaz:
http://arxiv.org/abs/2405.16533
Autor:
Shi, Zhengliang, Gao, Shen, Chen, Xiuyi, Feng, Yue, Yan, Lingyong, Shi, Haibo, Yin, Dawei, Ren, Pengjie, Verberne, Suzan, Ren, Zhaochun
Tool learning empowers large language models (LLMs) as agents to use external tools and extend their utility. Existing methods employ one single LLM-based agent to iteratively select and execute tools, thereafter incorporating execution results into
Externí odkaz:
http://arxiv.org/abs/2403.03031
This study proposes a class of augmented subspace schemes for the weak Galerkin (WG) finite element method used to solve eigenvalue problems. The augmented subspace is built with the conforming linear finite element space defined on the coarse mesh a
Externí odkaz:
http://arxiv.org/abs/2401.04063
Autor:
Jin, Jiarui, Chen, Xianyu, Ye, Fanghua, Yang, Mengyue, Feng, Yue, Zhang, Weinan, Yu, Yong, Wang, Jun
Recommender systems trained on offline historical user behaviors are embracing conversational techniques to online query user preference. Unlike prior conversational recommendation approaches that systemically combine conversational and recommender p
Externí odkaz:
http://arxiv.org/abs/2310.04230
Recently, the development of large language models (LLMs) has been significantly enhanced the question answering and dialogue generation, and makes them become increasingly popular in current practical scenarios. While unlike the general dialogue sys
Externí odkaz:
http://arxiv.org/abs/2309.08949
Embedding polygonal mesh assets within photorealistic Neural Radience Fields (NeRF) volumes, such that they can be rendered and their dynamics simulated in a physically consistent manner with the NeRF, is under-explored from the system perspective of
Externí odkaz:
http://arxiv.org/abs/2309.04581
Autor:
Jierong Chen, Zi-Yue Li, Guansheng Zheng, Lixue Cao, Yun-Miao Guo, Qizhou Lian, Bing Gu, Cai-Feng Yue
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-16 (2024)
Abstract This study investigates the role of RNF4-mediated ubiquitination and degradation of PDHA1 in colorectal cancer (CRC) metabolism and metastasis. Integrating (The Cancer Genome Atlas) TCGA and Clinical Proteomic Tumor Analysis Consortium (CPTA
Externí odkaz:
https://doaj.org/article/ece11b2673c04090b11a20271e2cbac4
