Zobrazeno 1 - 10
of 1 640
pro vyhledávání: '"Li, jinpeng"'
Autor:
Wu, Pengfei, Liu, Jiahao, Gong, Zhuocheng, Wang, Qifan, Li, Jinpeng, Wang, Jingang, Cai, Xunliang, Zhao, Dongyan
Publikováno v:
NLPCC2024
Recent advancements in Large Language Models (LLMs) have shown remarkable performance across a wide range of tasks. Despite this, the auto-regressive nature of LLM decoding, which generates only a single token per forward propagation, fails to fully
Externí odkaz:
http://arxiv.org/abs/2410.20488
Breast cancer is a significant threat to human health. Contrastive learning has emerged as an effective method to extract critical lesion features from mammograms, thereby offering a potent tool for breast cancer screening and analysis. A crucial asp
Externí odkaz:
http://arxiv.org/abs/2409.15745
Mammography is the primary imaging tool for breast cancer diagnosis. Despite significant strides in applying deep learning to interpret mammography images, efforts that focus predominantly on visual features often struggle with generalization across
Externí odkaz:
http://arxiv.org/abs/2409.15744
Electroencephalography (EEG)-based emotion recognition has gained significant traction due to its accuracy and objectivity. However, the non-stationary nature of EEG signals leads to distribution drift over time, causing severe performance degradatio
Externí odkaz:
http://arxiv.org/abs/2409.15733
Whisper and other large-scale automatic speech recognition models have made significant progress in performance. However, their performance on many low-resource languages, such as Kazakh, is not satisfactory. It is worth researching how to utilize lo
Externí odkaz:
http://arxiv.org/abs/2408.05554
Autor:
Du, Changde, Fu, Kaicheng, Wen, Bincheng, Sun, Yi, Peng, Jie, Wei, Wei, Gao, Ying, Wang, Shengpei, Zhang, Chuncheng, Li, Jinpeng, Qiu, Shuang, Chang, Le, He, Huiguang
The conceptualization and categorization of natural objects in the human mind have long intrigued cognitive scientists and neuroscientists, offering crucial insights into human perception and cognition. Recently, the rapid development of Large Langua
Externí odkaz:
http://arxiv.org/abs/2407.01067
Autor:
Yang, Yifan, Song, Zheshu, Zhuo, Jianheng, Cui, Mingyu, Li, Jinpeng, Yang, Bo, Du, Yexing, Ma, Ziyang, Liu, Xunying, Wang, Ziyuan, Li, Ke, Fan, Shuai, Yu, Kai, Zhang, Wei-Qiang, Chen, Guoguo, Chen, Xie
The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, which is scarce for low-resource languages. This paper presents GigaSpe
Externí odkaz:
http://arxiv.org/abs/2406.11546
Most large language models (LLMs) are sensitive to prompts, and another synonymous expression or a typo may lead to unexpected results for the model. Composing an optimal prompt for a specific demand lacks theoretical support and relies entirely on h
Externí odkaz:
http://arxiv.org/abs/2406.10950
The advent of large language models (LLMs) has facilitated the development of natural language text generation. It also poses unprecedented challenges, with content hallucination emerging as a significant concern. Existing solutions often involve exp
Externí odkaz:
http://arxiv.org/abs/2406.03075
Autor:
Wang, Jiaze, Chen, Hao, Xu, Hongcan, Li, Jinpeng, Wang, Bowen, Shao, Kun, Liu, Furui, Chen, Huaxi, Chen, Guangyong, Heng, Pheng-Ann
Weather forecasting plays a critical role in various sectors, driving decision-making and risk management. However, traditional methods often struggle to capture the complex dynamics of meteorological systems, particularly in the presence of high-res
Externí odkaz:
http://arxiv.org/abs/2405.18849