Zobrazeno 1 - 10
of 214
pro vyhledávání: '"ZHONG Zhiqiang"'
Publikováno v:
Fenmo yejin jishu, Vol 42, Iss 2, Pp 184-191 (2024)
Inhomogeneous structure WC−6Co cemented carbides with the different Y2O3 additions (mass fraction) were prepared by low pressure sintering. The microstructure and properties of the cemented carbides were investigated by scanning electron microscope
Externí odkaz:
https://doaj.org/article/b05fd34239ac4656a6b269f2f72683c1
Publikováno v:
Shuitu Baochi Xuebao, Vol 38, Iss 2, Pp 157-164 (2024)
[Objective] To investigate the effects of biological crustal cover and freeze-thaw on soil structure. [Methods] The effects of different freeze-thaw times, initial soil water content before freeze-thaw and biological crusting (algae crust) cover on s
Externí odkaz:
https://doaj.org/article/3b2a6fcdbc2843ebb718bd9d0939a898
Publikováno v:
Open Chemistry, Vol 21, Iss 1, Pp 1924-50 (2023)
Herein, the bio-inspired synthesis of Au nanoparticles (NPs) adorned Thymbra spicata extract functionalized Fe3O4 NPs as a novel magnetic nanocomposite has been demonstrated. The plant phytochemicals act as a natural and non-toxic reductant as well a
Externí odkaz:
https://doaj.org/article/7d6470af60a14d978eb25ca1837c1a5f
This report presents our method for Single Object Tracking (SOT), which aims to track a specified object throughout a video sequence. We employ the LoRAT method. The essence of the work lies in adapting LoRA, a technique that fine-tunes a small subse
Externí odkaz:
http://arxiv.org/abs/2410.16329
Autor:
Zhong, Zhiqiang, Mottin, Davide
Large Language Models (LLMs) have shown remarkable capabilities in processing various data structures, including graphs. While previous research has focused on developing textual encoding methods for graph representation, the emergence of multimodal
Externí odkaz:
http://arxiv.org/abs/2409.08864
Large Language Models (LLMs) stand at the forefront of a number of Natural Language Processing (NLP) tasks. Despite the widespread adoption of LLMs in NLP, much of their potential in broader fields remains largely unexplored, and significant limitati
Externí odkaz:
http://arxiv.org/abs/2403.05075
Autor:
Zhong, Zhiqiang, Mottin, Davide
Predicting protein properties is paramount for biological and medical advancements. Current protein engineering mutates on a typical protein, called the wild-type, to construct a family of homologous proteins and study their properties. Yet, existing
Externí odkaz:
http://arxiv.org/abs/2402.13418
As Machine Learning (ML) models grow in size and demand higher-quality training data, the expenses associated with re-training and fine-tuning these models are escalating rapidly. Inspired by recent impressive achievements of Large Language Models (L
Externí odkaz:
http://arxiv.org/abs/2402.13414
Proposed as a solution to the inherent black-box limitations of graph neural networks (GNNs), post-hoc GNN explainers aim to provide precise and insightful explanations of the behaviours exhibited by trained GNNs. Despite their recent notable advance
Externí odkaz:
http://arxiv.org/abs/2309.01706
Self-explainable deep neural networks are a recent class of models that can output ante-hoc local explanations that are faithful to the model's reasoning, and as such represent a step forward toward filling the gap between expressiveness and interpre
Externí odkaz:
http://arxiv.org/abs/2308.15096