Zobrazeno 1 - 10
of 541
pro vyhledávání: '"XU Ruifeng"'
Publikováno v:
智慧农业, Vol 6, Iss 2, Pp 62-71 (2024)
ObjectiveIn recent years, there has been a steady increase in the occurrence and fatality rates of shrimp diseases, causing substantial impacts in shrimp aquaculture. These diseases are marked by their swift onset, high infectivity, complex control r
Externí odkaz:
https://doaj.org/article/fa5edbf7a5754eec8933cc9a7b3efa54
Model merging has gained increasing attention as an efficient and effective technique for integrating task-specific weights from various tasks into a unified multi-task model without retraining or additional data. As a representative approach, Task A
Externí odkaz:
http://arxiv.org/abs/2411.18729
Idioms represent a ubiquitous vehicle for conveying sentiments in the realm of everyday discourse, rendering the nuanced analysis of idiom sentiment crucial for a comprehensive understanding of emotional expression within real-world texts. Neverthele
Externí odkaz:
http://arxiv.org/abs/2409.17588
The success of Large Language Models (LLMs) relies heavily on the huge amount of pre-training data learned in the pre-training phase. The opacity of the pre-training process and the training data causes the results of many benchmark tests to become u
Externí odkaz:
http://arxiv.org/abs/2409.01790
Large Language Models (LLMs) have demonstrated exceptional performance across various natural language processing tasks, yet they occasionally tend to yield content that factually inaccurate or discordant with the expected output, a phenomenon empiri
Externí odkaz:
http://arxiv.org/abs/2408.08769
Autor:
Lin, Jiayu, Chen, Guanrong, Jin, Bojun, Li, Chenyang, Jia, Shutong, Lin, Wancong, Sun, Yang, He, Yuhang, Yang, Caihua, Bao, Jianzhu, Wu, Jipeng, Su, Wen, Chen, Jinglu, Li, Xinyi, Chen, Tianyu, Han, Mingjie, Du, Shuaiwen, Wang, Zijian, Li, Jiyin, Suo, Fuzhong, Wang, Hao, Lin, Nuanchen, Huang, Xuanjing, Jiang, Changjian, Xu, RuiFeng, Zhang, Long, Cao, Jiuxin, Jin, Ting, Wei, Zhongyu
In this paper we present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023), and introduce the related datasets. We organize two tracks to handle the argumentative generation tasks in different
Externí odkaz:
http://arxiv.org/abs/2407.14829
Publikováno v:
智慧农业, Vol 2, Iss 4, Pp 79-88 (2020)
In order to improve the efficiency and safety of epidemic prevention and disinfection operations for livestock and poultry breeding, the disinfection robot system and the automatic disinfecting mode were researched in this study. The robot system is
Externí odkaz:
https://doaj.org/article/a589c48e1bd44565bfdd85d2b6a422e9
Aspect Sentiment Quad Prediction (ASQP) aims to predict all quads (aspect term, aspect category, opinion term, sentiment polarity) for a given review, which is the most representative and challenging task in aspect-based sentiment analysis. A key cha
Externí odkaz:
http://arxiv.org/abs/2406.18078
Autor:
Liu, Ziqiang, Fang, Feiteng, Feng, Xi, Du, Xinrun, Zhang, Chenhao, Wang, Zekun, Bai, Yuelin, Zhao, Qixuan, Fan, Liyang, Gan, Chengguang, Lin, Hongquan, Li, Jiaming, Ni, Yuansheng, Wu, Haihong, Narsupalli, Yaswanth, Zheng, Zhigang, Li, Chengming, Hu, Xiping, Xu, Ruifeng, Chen, Xiaojun, Yang, Min, Liu, Jiaheng, Liu, Ruibo, Huang, Wenhao, Zhang, Ge, Ni, Shiwen
The rapid advancements in the development of multimodal large language models (MLLMs) have consistently led to new breakthroughs on various benchmarks. In response, numerous challenging and comprehensive benchmarks have been proposed to more accurate
Externí odkaz:
http://arxiv.org/abs/2406.05862
Large language models (LLMs) have achieved promising results in sentiment analysis through the in-context learning (ICL) paradigm. However, their ability to distinguish subtle sentiments still remains a challenge. Inspired by the human ability to adj
Externí odkaz:
http://arxiv.org/abs/2406.02911