Zobrazeno 1 - 10
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pro vyhledávání: '"PAN, Bo"'
Representation learning of Text-Attributed Graphs (TAGs) has garnered significant attention due to its applications in various domains, including recommendation systems and social networks. Despite advancements in TAG learning methodologies, challeng
Externí odkaz:
http://arxiv.org/abs/2410.15268
Autor:
Wang, Senmao, Gong, Haifan, Cui, Runmeng, Wan, Boyao, Liu, Yicheng, Hu, Zhonglin, Yang, Haiqing, Zhou, Jingyang, Pan, Bo, Lin, Lin, Jiang, Haiyue
Costal cartilage segmentation is crucial to various medical applications, necessitating precise and reliable techniques due to its complex anatomy and the importance of accurate diagnosis and surgical planning. We propose a novel deep learning-based
Externí odkaz:
http://arxiv.org/abs/2408.07444
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum of real-world scenarios. Despite the potential for deeper insights, ex
Externí odkaz:
http://arxiv.org/abs/2405.16800
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in many applications such as citation graphs, social media, and knowledge
Externí odkaz:
http://arxiv.org/abs/2405.16506
Generating data with properties of interest by external users while following the right causation among its intrinsic factors is important yet has not been well addressed jointly. This is due to the long-lasting challenge of jointly identifying key l
Externí odkaz:
http://arxiv.org/abs/2405.16219
Autor:
Pan, Bo, Lu, Jiaying, Wang, Ke, Zheng, Li, Wen, Zhen, Feng, Yingchaojie, Zhu, Minfeng, Chen, Wei
The potential of automatic task-solving through Large Language Model (LLM)-based multi-agent collaboration has recently garnered widespread attention from both the research community and industry. While utilizing natural language to coordinate multip
Externí odkaz:
http://arxiv.org/abs/2404.11943
Autor:
Sun, Hui, Pan, Bo, Yang, Zhening, Krajewski, Adam M., Bocklund, Brandon, Shang, Shun-Li, Li, Jingjing, Beese, Allison M., Liu, Zi-Kui
Publikováno v:
Materialia, Volume 36, August 2024, 102153
Assembly of dissimilar metals can be achieved by different methods, for example, casting, welding, and additive manufacturing (AM). However, undesired phases formed in liquid-phase assembling processes due to solute segregation during solidification
Externí odkaz:
http://arxiv.org/abs/2403.19084
The deployment and application of Large Language Models (LLMs) is hindered by their memory inefficiency, computational demands, and the high costs of API inferences. Traditional distillation methods, which transfer the capabilities of LLMs to smaller
Externí odkaz:
http://arxiv.org/abs/2402.13098
Text-Attributed Graphs (TAGs) are graphs of connected textual documents. Graph models can efficiently learn TAGs, but their training heavily relies on human-annotated labels, which are scarce or even unavailable in many applications. Large language m
Externí odkaz:
http://arxiv.org/abs/2402.12022
Recently, Large Language Model based Autonomous system(LLMAS) has gained great popularity for its potential to simulate complicated behaviors of human societies. One of its main challenges is to present and analyze the dynamic events evolution of LLM
Externí odkaz:
http://arxiv.org/abs/2402.08995