Zobrazeno 1 - 10
of 243
pro vyhledávání: '"Zhang, Meishan"'
Autor:
Zhang, Xin, Zhang, Yanzhao, Long, Dingkun, Xie, Wen, Dai, Ziqi, Tang, Jialong, Lin, Huan, Yang, Baosong, Xie, Pengjun, Huang, Fei, Zhang, Meishan, Li, Wenjie, Zhang, Min
We present systematic efforts in building long-context multilingual text representation model (TRM) and reranker from scratch for text retrieval. We first introduce a text encoder (base size) enhanced with RoPE and unpadding, pre-trained in a native
Externí odkaz:
http://arxiv.org/abs/2407.19669
Publikováno v:
[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
While pre-training large-scale video-language models (VLMs) has shown remarkable potential for various downstream video-language tasks, existing VLMs can still suffer from certain commonly seen limitations, e.g., coarse-grained cross-modal aligning ,
Externí odkaz:
http://arxiv.org/abs/2406.19255
Opinion Expression Identification (OEI) is essential in NLP for applications ranging from voice assistants to depression diagnosis. This study extends OEI to encompass multimodal inputs, underlining the significance of auditory cues in delivering emo
Externí odkaz:
http://arxiv.org/abs/2406.18088
Autor:
Chen, Huiyao, Zhao, Yu, Chen, Zulong, Wang, Mengjia, Li, Liangyue, Zhang, Meishan, Zhang, Min
Hierarchical text classification (HTC) is an important task with broad applications, while few-shot HTC has gained increasing interest recently. While in-context learning (ICL) with large language models (LLMs) has achieved significant success in few
Externí odkaz:
http://arxiv.org/abs/2406.17534
Autor:
Wang, Yidong, Guo, Qi, Yao, Wenjin, Zhang, Hongbo, Zhang, Xin, Wu, Zhen, Zhang, Meishan, Dai, Xinyu, Zhang, Min, Wen, Qingsong, Ye, Wei, Zhang, Shikun, Zhang, Yue
This paper introduces AutoSurvey, a speedy and well-organized methodology for automating the creation of comprehensive literature surveys in rapidly evolving fields like artificial intelligence. Traditional survey paper creation faces challenges due
Externí odkaz:
http://arxiv.org/abs/2406.10252
In the field of information extraction (IE), tasks across a wide range of modalities and their combinations have been traditionally studied in isolation, leaving a gap in deeply recognizing and analyzing cross-modal information. To address this, this
Externí odkaz:
http://arxiv.org/abs/2406.03701
Chinese sequence labeling tasks are heavily reliant on accurate word boundary demarcation. Although current pre-trained language models (PLMs) have achieved substantial gains on these tasks, they rarely explicitly incorporate boundary information int
Externí odkaz:
http://arxiv.org/abs/2404.05560
Autor:
Yu, Jingsi, Kong, Cunliang, Yang, Liner, Zhang, Meishan, Zhu, Lin, Wang, Yujie, Lin, Haozhe, Sun, Maosong, Yang, Erhong
Sentence Pattern Structure (SPS) parsing is a syntactic analysis method primarily employed in language teaching.Existing SPS parsers rely heavily on textbook corpora for training, lacking cross-domain capability.To overcome this constraint, this pape
Externí odkaz:
http://arxiv.org/abs/2402.16311
Publikováno v:
ICASSP 2024
In nested Named entity recognition (NER), entities are nested with each other, and thus requiring more data annotations to address. This leads to the development of few-shot nested NER, where the prevalence of pretrained language models with in-conte
Externí odkaz:
http://arxiv.org/abs/2402.01182
Text ranking is a critical task in information retrieval. Recent advances in pre-trained language models (PLMs), especially large language models (LLMs), present new opportunities for applying them to text ranking. While supervised fine-tuning (SFT)
Externí odkaz:
http://arxiv.org/abs/2311.16720