Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Zheng, Yuanhang"'
Relation Extraction (RE) serves as a crucial technology for transforming unstructured text into structured information, especially within the framework of Knowledge Graph development. Its importance is emphasized by its essential role in various down
Externí odkaz:
http://arxiv.org/abs/2406.11162
Publikováno v:
In Proceedings of LREC-COLING 2024, pages 16263-16273
Tool learning aims to extend the capabilities of large language models (LLMs) with external tools. A major challenge in tool learning is how to support a large number of tools, including unseen tools. To address this challenge, previous studies have
Externí odkaz:
http://arxiv.org/abs/2403.06551
Autor:
Maimaiti, Mieradilijiang, Zheng, Yuanhang, Zhang, Ji, Huang, Fei, Zhang, Yue, Luo, Wenpei, Huang, Kaiyu
Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario. The demands for a cross-lingual smart-customer-service system for an e-commerce platform or some particular bus
Externí odkaz:
http://arxiv.org/abs/2403.01364
Despite intensive efforts devoted to tool learning, the problem of budget-constrained tool learning, which focuses on resolving user queries within a specific budget constraint, has been widely overlooked. This paper proposes a novel method for budge
Externí odkaz:
http://arxiv.org/abs/2402.15960
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 32 (2024) 3002-3013
Black-box prompt tuning employs derivative-free optimization algorithms to learn prompts within low-dimensional subspaces rather than back-propagating through the network of Large Language Models (LLMs). Recent studies reveal that black-box prompt tu
Externí odkaz:
http://arxiv.org/abs/2305.03518
In the field of medical CT image processing, convolutional neural networks (CNNs) have been the dominant technique.Encoder-decoder CNNs utilise locality for efficiency, but they cannot simulate distant pixel interactions properly.Recent research indi
Externí odkaz:
http://arxiv.org/abs/2211.00700
Text classification struggles to generalize to unseen classes with very few labeled text instances per class. In such a few-shot learning (FSL) setting, metric-based meta-learning approaches have shown promising results. Previous studies mainly aim t
Externí odkaz:
http://arxiv.org/abs/2204.04952
Contrastive learning (CL) has become a ubiquitous approach for several natural language processing (NLP) downstream tasks, especially for question answering (QA). However, the major challenge, how to efficiently train the knowledge retrieval model in
Externí odkaz:
http://arxiv.org/abs/2203.16187
Autor:
Sheng, Zhimei, Wang, Xuejie, Ding, Xiaodi, Zheng, Yuanhang, Guo, Ai, Cui, Jiayu, Ma, Jing, Duan, Wanli, Dong, Hao, Zhang, Hongxing, Cui, Meimei, Su, Wenxia, Zhang, Baogang
Publikováno v:
In Cellular Signalling July 2024 119
Publikováno v:
In Applied Soft Computing September 2024 162