Zobrazeno 1 - 10
of 190
pro vyhledávání: '"ZHANG Linhai"'
Publikováno v:
Xibei Gongye Daxue Xuebao, Vol 41, Iss 1, Pp 18-27 (2023)
The internal leakage fault-tolerant control problem of the electro-hydraulic servo actuator under the influence of multiple unmodeled dynamics is investigated in this paper, and an adaptive fault-tolerant control scheme based on unmodeled dynamics es
Externí odkaz:
https://doaj.org/article/114b0cc42811477c829f0b3db0460962
Due to the sparsity of user data, sentiment analysis on user reviews in e-commerce platforms often suffers from poor performance, especially when faced with extremely sparse user data or long-tail labels. Recently, the emergence of LLMs has introduce
Externí odkaz:
http://arxiv.org/abs/2403.06139
Despite the notable advancements of existing prompting methods, such as In-Context Learning and Chain-of-Thought for Large Language Models (LLMs), they still face challenges related to various biases. Traditional debiasing methods primarily focus on
Externí odkaz:
http://arxiv.org/abs/2403.02738
Conventional multi-hop fact verification models are prone to rely on spurious correlations from the annotation artifacts, leading to an obvious performance decline on unbiased datasets. Among the various debiasing works, the causal inference-based me
Externí odkaz:
http://arxiv.org/abs/2403.02698
Though Large Language Models (LLMs) have demonstrated the powerful capabilities of few-shot learning through prompting methods, supervised training is still necessary for complex reasoning tasks. Because of their extensive parameters and memory consu
Externí odkaz:
http://arxiv.org/abs/2403.01165
Though notable progress has been made, neural-based aspect-based sentiment analysis (ABSA) models are prone to learn spurious correlations from annotation biases, resulting in poor robustness on adversarial data transformations. Among the debiasing s
Externí odkaz:
http://arxiv.org/abs/2403.01166
Few-shot named entity recognition (NER) aims at identifying named entities based on only few labeled instances. Current few-shot NER methods focus on leveraging existing datasets in the rich-resource domains which might fail in a training-from-scratc
Externí odkaz:
http://arxiv.org/abs/2210.05632
Autor:
Yang, Ping, Su, Zhinan, Tang, Kam W., Yang, Hong, Tang, Lele, Zhang, Linhai, Luo, Juhua, Huang, Jiafang, Hu, Minjie, Sun, Dongyao, Qiu, Guanglong
Publikováno v:
In Agriculture, Ecosystems and Environment 1 November 2024 375
Autor:
Yang, Ping, Chen, Guanpeng, Zhang, Linhai, Tong, Chuan, Yang, Hong, Zhu, Wanyi, Sun, Dongyao, Tan, Lishan, Hong, Yan, Tang, Kam W.
Publikováno v:
In Catena July 2024 242
Autor:
Yang, Ping, Lin, Yongxin, Yang, Hong, Tong, Chuan, Zhang, Linhai, Lai, Derrick Y.F., Sun, Dongyao, Tan, Lishan, Tang, Lele, Hong, Yan, Tang, Kam W.
Publikováno v:
In Journal of Hydrology June 2024 637