Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Xi Yadong"'
Autor:
Chen, Jing, Zhu, Xinyu, Yang, Cheng, Shi, Chufan, Xi, Yadong, Zhang, Yuxiang, Wang, Junjie, Pu, Jiashu, Zhang, Rongsheng, Yang, Yujiu, Feng, Tian
Generative AI has demonstrated unprecedented creativity in the field of computer vision, yet such phenomena have not been observed in natural language processing. In particular, large language models (LLMs) can hardly produce written works at the lev
Externí odkaz:
http://arxiv.org/abs/2406.11683
Autor:
Shen, Yongliang, Tan, Zeqi, Wu, Shuhui, Zhang, Wenqi, Zhang, Rongsheng, Xi, Yadong, Lu, Weiming, Zhuang, Yueting
Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks. To adopt prompt learning in the NER task, two kinds of methods have been explored from a pair of symmetric perspectives, populat
Externí odkaz:
http://arxiv.org/abs/2305.17104
Autor:
Chen, Weijie, Chang, Yongzhu, Zhang, Rongsheng, Pu, Jiashu, Chen, Guandan, Zhang, Le, Xi, Yadong, Chen, Yijiang, Su, Chang
Simile interpretation (SI) and simile generation (SG) are challenging tasks for NLP because models require adequate world knowledge to produce predictions. Previous works have employed many hand-crafted resources to bring knowledge-related into model
Externí odkaz:
http://arxiv.org/abs/2204.12807
Autor:
Luo, Ziyang, Xi, Yadong, Ma, Jing, Yang, Zhiwei, Mao, Xiaoxi, Fan, Changjie, Zhang, Rongsheng
Since 2017, the Transformer-based models play critical roles in various downstream Natural Language Processing tasks. However, a common limitation of the attention mechanism utilized in Transformer Encoder is that it cannot automatically capture the
Externí odkaz:
http://arxiv.org/abs/2204.08688
Image Captioning is a traditional vision-and-language task that aims to generate the language description of an image. Recent studies focus on scaling up the model size and the number of training data, which significantly increase the cost of model t
Externí odkaz:
http://arxiv.org/abs/2202.06574
Image Captioning is a fundamental task to join vision and language, concerning about cross-modal understanding and text generation. Recent years witness the emerging attention on image captioning. Most of existing works follow a traditional two-stage
Externí odkaz:
http://arxiv.org/abs/2201.12723
Autor:
Zhang, Rongsheng, Mao, Xiaoxi, Li, Le, Jiang, Lin, Chen, Lin, Hu, Zhiwei, Xi, Yadong, Fan, Changjie, Huang, Minlie
Recently, a variety of neural models have been proposed for lyrics generation. However, most previous work completes the generation process in a single pass with little human intervention. We believe that lyrics creation is a creative process with hu
Externí odkaz:
http://arxiv.org/abs/2201.06724
The wave of pre-training language models has been continuously improving the quality of the machine-generated conversations, however, some of the generated responses still suffer from excessive repetition, sometimes repeating words from utterance, so
Externí odkaz:
http://arxiv.org/abs/2112.08657
Autor:
Li, Gongzheng, Xi, Yadong, Ding, Jingzhen, Wang, Duan, Liu, Bai, Fan, Changjie, Mao, Xiaoxi, Zhao, Zeng
Recently, large-scale transformer-based models have been proven to be effective over various tasks across many domains. Nevertheless, applying them in industrial production requires tedious and heavy works to reduce inference costs. To fill such a ga
Externí odkaz:
http://arxiv.org/abs/2104.12470
Recent advances in open-domain dialogue systems rely on the success of neural models that are trained on large-scale data. However, collecting large-scale dialogue data is usually time-consuming and labor-intensive. To address this data dilemma, we p
Externí odkaz:
http://arxiv.org/abs/2009.09427