Zobrazeno 1 - 10
of 184 653
pro vyhledávání: '"Zhiqiang AN"'
LLMs can exhibit age biases, resulting in unequal treatment of individuals across age groups. While much research has addressed racial and gender biases, age bias remains little explored. The scarcity of instruction-tuning and preference datasets for
Externí odkaz:
http://arxiv.org/abs/2409.04340
The human brain exhibits a strong ability to spontaneously associate different visual attributes of the same or similar visual scene, such as associating sketches and graffiti with real-world visual objects, usually without supervising information. I
Externí odkaz:
http://arxiv.org/abs/2409.18694
Autor:
Yang, Jinlong, Shang, Hengchao, Wei, Daimeng, Guo, Jiaxin, Li, Zongyao, Wu, Zhanglin, Rao, Zhiqiang, Li, Shaojun, Xie, Yuhao, Luo, Yuanchang, Zheng, Jiawei, Wei, Bin, Yang, Hao
This paper describes the submissions of Huawei Translation Services Center(HW-TSC) to WMT24 chat translation shared task on English$\leftrightarrow$Germany (en-de) bidirection. The experiments involved fine-tuning models using chat data and exploring
Externí odkaz:
http://arxiv.org/abs/2409.16331
Autor:
Yan, Zhen, Shen, Zhiqiang, Jiang, Peng, Zhang, Bo, Zhang, Haiyan, Cui, Lang, Luo, Jintao, Chen, Rurong, Jiang, Wu, Zhang, Hua, Wu, De, Zhao, Rongbing, Yuan, Jianping, Hu, Yue, Wu, Yajun, Xia, Bo, Li, Guanghui, Rao, Yongnan, Chen, Chenyu, Wang, Xiaowei, Ding, Hao, Liu, Yongpeng, Zhang, Fuchen, Jiang, Yongbin
The importance of Very Long Baseline Interferometry (VLBI) for pulsar research is becoming increasingly prominent and receiving more and more attention. In this paper, we present pathfinding pulsar observation results with the Chinese VLBI Network (C
Externí odkaz:
http://arxiv.org/abs/2409.16059
Autor:
Luo, Yuanchang, Wu, Zhanglin, Wei, Daimeng, Shang, Hengchao, Li, Zongyao, Guo, Jiaxin, Rao, Zhiqiang, Li, Shaojun, Yang, Jinlong, Xie, Yuhao, Wei, Jiawei Zheng Bin, Yang, Hao
This article introduces the submission status of the Translation into Low-Resource Languages of Spain task at (WMT 2024) by Huawei Translation Service Center (HW-TSC). We participated in three translation tasks: spanish to aragonese (es-arg), spanish
Externí odkaz:
http://arxiv.org/abs/2409.15924
Autor:
Wei, Bin, Zhen, Jiawei, Li, Zongyao, Wu, Zhanglin, Wei, Daimeng, Guo, Jiaxin, Rao, Zhiqiang, Li, Shaojun, Luo, Yuanchang, Shang, Hengchao, Yang, Jinlong, Xie, Yuhao, Yang, Hao
This paper introduces the submission by Huawei Translation Center (HW-TSC) to the WMT24 Indian Languages Machine Translation (MT) Shared Task. To develop a reliable machine translation system for low-resource Indian languages, we employed two distinc
Externí odkaz:
http://arxiv.org/abs/2409.15879
Autor:
Luo, Yuanchang, Guo, Jiaxin, Wei, Daimeng, Shang, Hengchao, Li, Zongyao, Wu, Zhanglin, Rao, Zhiqiang, Li, Shaojun, Yang, Jinlong, Yang, Hao
This report outlines our approach for the WMT24 Discourse-Level Literary Translation Task, focusing on the Chinese-English language pair in the Constrained Track. Translating literary texts poses significant challenges due to the nuanced meanings, id
Externí odkaz:
http://arxiv.org/abs/2409.16539
Autor:
Wu, Zhanglin, Wei, Daimeng, Li, Zongyao, Shang, Hengchao, Guo, Jiaxin, Li, Shaojun, Rao, Zhiqiang, Luo, Yuanchang, Xie, Ning, Yang, Hao
This paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT24 general machine translation (MT) shared task, where we participate in the English to Chinese (en2zh) language pair. Similar to previous years' work, we use t
Externí odkaz:
http://arxiv.org/abs/2409.14800
Confidential Virtual Machines (CVMs) are a type of VMbased Trusted Execution Environments (TEEs) designed to enhance the security of cloud-based VMs, safeguarding them even from malicious hypervisors. Although CVMs have been widely adopted by major c
Externí odkaz:
http://arxiv.org/abs/2409.15542
Referring Expression Comprehension (REC), which aims to ground a local visual region via natural language, is a task that heavily relies on multimodal alignment. Most existing methods utilize powerful pre-trained models to transfer visual/linguistic
Externí odkaz:
http://arxiv.org/abs/2409.13609