Zobrazeno 1 - 10
of 2 206
pro vyhledávání: '"Hu Junjie"'
Publikováno v:
Open Medicine, Vol 19, Iss 1, Pp 452-65 (2024)
Metastasis significantly contributes to the poor prognosis of advanced nasopharyngeal carcinoma (NPC). Our prior studies have demonstrated a decrease in BIRC5-206 expression in NPC, which promotes disease progression. However, the role of BIRC5-206 i
Externí odkaz:
https://doaj.org/article/e16403dd062a415fb57b8d71f14b276d
Publikováno v:
Dizhi lixue xuebao, Vol 28, Iss 2, Pp 203-216 (2022)
The Ounan depression is a favorable structural unit for the Carboniferous hydrocarbon migration and accumulation, which demonstrates certain exploration potential. However, the organic matter enrichment mechanism is still unclear, which results in th
Externí odkaz:
https://doaj.org/article/0dcd01c188444f4d9523106664a4c991
Mining attacks enable an adversary to procure a disproportionately large portion of mining rewards by deviating from honest mining practices within the PoW-based blockchain system. In this paper, we demonstrate that the security vulnerabilities of Po
Externí odkaz:
http://arxiv.org/abs/2411.06187
Autor:
Syamkumar, Anand, Tseng, Nora, Barron, Kaycie, Yang, Shanglin, Karumbaiah, Shamya, Uppal, Rheeya, Hu, Junjie
Large language models (LLMs) offer promise in generating educational content, providing instructor feedback, and reducing teacher workload on assessments. While prior studies have focused on studying LLM-powered learning analytics, limited research h
Externí odkaz:
http://arxiv.org/abs/2411.04308
The conventional paradigm of using large language models (LLMs) for evaluating natural language generation (NLG) systems typically relies on two key inputs: (1) a clear definition of the NLG task to be evaluated and (2) a list of pre-defined evaluati
Externí odkaz:
http://arxiv.org/abs/2410.10724
The rapid advances of multi-modal agents built on large foundation models have largely overlooked their potential for language-based communication between agents in collaborative tasks. This oversight presents a critical gap in understanding their ef
Externí odkaz:
http://arxiv.org/abs/2410.07553
Federated learning holds great potential for enabling large-scale healthcare research and collaboration across multiple centres while ensuring data privacy and security are not compromised. Although numerous recent studies suggest or utilize federate
Externí odkaz:
http://arxiv.org/abs/2409.09727
In recent years, unmanned aerial vehicles (UAVs) have played an increasingly crucial role in supporting disaster emergency response efforts by analyzing aerial images. While current deep-learning models focus on improving accuracy, they often overloo
Externí odkaz:
http://arxiv.org/abs/2409.00510
Much work on the cultural awareness of large language models (LLMs) focuses on the models' sensitivity to geo-cultural diversity. However, in addition to cross-cultural differences, there also exists common ground across cultures. For instance, a bri
Externí odkaz:
http://arxiv.org/abs/2408.05102
Autor:
Chuang, Yun-Shiuan, Nirunwiroj, Krirk, Studdiford, Zach, Goyal, Agam, Frigo, Vincent V., Yang, Sijia, Shah, Dhavan, Hu, Junjie, Rogers, Timothy T.
Publikováno v:
Findings of the Association for Computational Linguistics (ACL): EMNLP 2024
Creating human-like large language model (LLM) agents is crucial for faithful social simulation. Having LLMs role-play based on demographic information sometimes improves human likeness but often does not. This study assessed whether LLM alignment wi
Externí odkaz:
http://arxiv.org/abs/2406.17232