Zobrazeno 1 - 10
of 49
pro vyhledávání: '"yang, Liner"'
Fact verification tasks aim to identify the integrity of textual contents according to the truthful corpus. Existing fact verification models usually build a fully connected reasoning graph, which regards claim-evidence pairs as nodes and connects th
Externí odkaz:
http://arxiv.org/abs/2405.10481
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
Autor:
Lu, Luming, An, Jiyuan, Wang, Yujie, yang, Liner, Kong, Cunliang, Liu, Zhenghao, Wang, Shuo, Lin, Haozhe, Fang, Mingwei, Huang, Yaping, Yang, Erhong
Natural Language Processing (NLP) technologies have revolutionized the way we interact with information systems, with a significant focus on converting natural language queries into formal query languages such as SQL. However, less emphasis has been
Externí odkaz:
http://arxiv.org/abs/2402.13740
Autor:
Liu, Yang, Xu, Meng, Wang, Shuo, Yang, Liner, Wang, Haoyu, Liu, Zhenghao, Kong, Cunliang, Chen, Yun, Sun, Maosong, Yang, Erhong
Modern large language models (LLMs) should generally benefit individuals from various cultural backgrounds around the world. However, most recent advanced generative evaluation benchmarks tailed for LLMs mainly focus on English. To this end, we intro
Externí odkaz:
http://arxiv.org/abs/2402.13524
Autor:
Wang, Haoyu, Wang, Shuo, Yan, Yukun, Wang, Xujia, Yang, Zhiyu, Xu, Yuzhuang, Liu, Zhenghao, Yang, Liner, Ding, Ning, Han, Xu, Liu, Zhiyuan, Sun, Maosong
Open-source large language models (LLMs) have gained significant strength across diverse fields. Nevertheless, the majority of studies primarily concentrate on English, with only limited exploration into the realm of multilingual abilities. In this w
Externí odkaz:
http://arxiv.org/abs/2402.04588
Autor:
Liu, Pengjie, Liu, Zhenghao, Yi, Xiaoyuan, Yang, Liner, Wang, Shuo, Gu, Yu, Yu, Ge, Xie, Xing, Yang, Shuang-hua
Most existing Legal Judgment Prediction (LJP) models focus on discovering the legal triggers in the criminal fact description. However, in real-world scenarios, a professional judge not only needs to assimilate the law case experience that thrives on
Externí odkaz:
http://arxiv.org/abs/2401.15371
Autor:
Chong, Ruining, Lu, Luming, Yang, Liner, Nie, Jinran, Liu, Zhenghao, Wang, Shuo, Zhou, Shuhan, Li, Yaoxin, Yang, Erhong
Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long time. The lack of generic evaluation data is an essential reason for t
Externí odkaz:
http://arxiv.org/abs/2306.02796
Autor:
Wang, Yujie, Huang, Chao, Yang, Liner, Fang, Zhixuan, Huang, Yaping, Liu, Yang, Yu, Jingsi, Yang, Erhong
This paper introduces a novel crowdsourcing worker selection algorithm, enhancing annotation quality and reducing costs. Unlike previous studies targeting simpler tasks, this study contends with the complexities of label interdependencies in sequence
Externí odkaz:
http://arxiv.org/abs/2305.06683
Text generation rarely considers the control of lexical complexity, which limits its more comprehensive practical application. We introduce a novel task of lexical complexity controlled sentence generation, which aims at keywords to sentence generati
Externí odkaz:
http://arxiv.org/abs/2211.14540
The definition generation task aims to generate a word's definition within a specific context automatically. However, owing to the lack of datasets for different complexities, the definitions produced by models tend to keep the same complexity level.
Externí odkaz:
http://arxiv.org/abs/2209.14614