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检索条件"任意字段=23rd Conference on Computational Natural Language Learning, CoNLL 2019"
100 条 记 录,以下是1-10 订阅
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conll 2019 - 23rd conference on computational natural language learning, Proceedings of the conference
CoNLL 2019 - 23rd Conference on Computational Natural Langua...
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23rd conference on computational natural language learning, conll 2019
The proceedings contain 97 papers. The topics discussed include: analyzing neural language models: contextual decomposition reveals default reasoning in number and gender assignment;deconstructing supertagging into mu...
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conll 2019 - SIGNLL conference on computational natural language learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 conference on natural language learning
CoNLL 2019 - SIGNLL Conference on Computational Natural Lang...
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2019 Shared Task on Cross-Framework Meaning Representation Parsing, MRP 2019 at the 23rd conference for computational language learning, conll 2019
The proceedings contain 16 papers. The topics discussed include: SJTU-NICT at MRP2019: multi-task learning for end-to-end uniform semantic graph parsing;the ERG at MRP 2019: radically compositional semantic dependenci...
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Overview of CCL24-Eval Task 4: The Fourth Chinese Abstract Meaning Representation Parsing Evaluation  23
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23rd Chinese National conference on computational Linguistics, CCL 2024
作者: Xu, Zhixing Zhang, Yixuan Li, Bin Zhou, Junsheng Qu, Weiguang School of Chinese Language and Literature Nanjing Normal University China Center for Language Big Data and Computational Humanities Nanjing Normal University China School of Computer and Electronic Information Nanjing Normal University China
Meaning Representation has become a key research area in sentence-level semantic parsing within natural language processing. Substantial progress has been achieved in various NLP tasks using AMR. This paper presents t... 详细信息
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Overview of CCL24-Eval Task 5: Classical Chinese Historical Event Detection Evaluation  23
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23rd Chinese National conference on computational Linguistics, CCL 2024
作者: Feng, Zhenbing Li, Wei Shao, Yanqiu Information Science School Beijing Language and Culture University China Language Resources Monitoring and Research Center 15 Xueyuan Road HaiDian District Beijing100083 China
Event detection involves identifying and extracting event information from natural language texts. The complex syntax and semantics of Classical Chinese, coupled with its limited usage, pose significant challenges for... 详细信息
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Prior Constraints-based Reward Model Training for Aligning Large language Models  23
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23rd Chinese National conference on computational Linguistics, CCL 2024
作者: Zhou, Hang Wang, Chenglong Hu, Yimin Xiao, Tong Zhang, Chunliang Zhu, Jingbo NLP Lab School of Computer Science and Engineering Northeastern University Shenyang China NiuTrans Research Shenyang China
Reinforcement learning with human feedback for aligning large language models (LLMs) trains a reward model typically using ranking loss with comparison pairs. However, the training procedure suffers from an inherent p... 详细信息
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LLM-based Sign language Production  23
LLM-based Sign Language Production
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23rd IEEE International conference on Machine learning and Applications, ICMLA 2024
作者: Silveira, Wellington Mendonça, Luca De Bem, Rodrigo Federal University of Rio Grande Center of Computational Sciences Rio Grande Brazil
Sign language is an effective means of communication for individuals with different degrees of hearing impairment. Assistive technologies are a significant ally in the social inclusion of people from these groups. Rec... 详细信息
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Overview of CCL24-Eval Task 10: Translation Quality Evaluation of Sign language Avatar  23
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23rd Chinese National conference on computational Linguistics, CCL 2024
作者: Zhao, Yuan Zhang, Ruiquan Yao, Dengfeng Chen, Yidong Beijing Key Laboratory of Information Service Engineering Beijing Union University China School of Informatics Xiamen University China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University China Lab of Computational Linguistics School of Humanities Tsinghua University China
Sign language Avatar technology aims to create virtual agents capable of communicating with deaf individuals through sign language, similar to the text dialogue agent ChatGPT but focusing on sign language communicatio... 详细信息
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Balancing and Contrasting Biased Samples for Debiased Visual Question Answering  23
Balancing and Contrasting Biased Samples for Debiased Visual...
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23rd IEEE International conference on Data Mining (IEEE ICDM)
作者: Cao, Runlin Li, Zhixin Guangxi Normal Univ Key Lab Educ Blockchain & Intelligent Technol Minist Educ Guilin 541004 Peoples R China Guangxi Normal Univ Guangxi Key Lab Multisource Informat Min & Secur Guilin 541004 Peoples R China
The goal of Visual Question Answering (VQA) is to test the reasoning ability of an intelligent agent by evaluating visual and textual information. However, recent studies suggest that many VQA models may only capture ... 详细信息
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Chinese Grammatical Error Correction via Large language Model Guided Optimization Training  23
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23rd Chinese National conference on computational Linguistics, CCL 2024
作者: Liu, Xiao Li, Ying Yu, Zhengtao Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Yunnan Key Laboratory of Artificial Intelligence Kunming China
Pre-trained language model-based methods for Chinese Grammatical Error Correction (CGEC) are categorized into Seq2Seq and Seq2Edit types. However, both Seq2Seq and Seq2Edit models depend on high-quality training data ... 详细信息
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OPEx: A Large language Model-Powered Framework for Embodied Instruction Following  23
OPEx: A Large Language Model-Powered Framework for Embodied ...
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23rd International conference on Autonomous Agents and Multiagent Systems, AAMAS 2024
作者: Shi, Haochen Sun, Zhiyuan Yuan, Xingdi Côté, Marc-Alexandre Liu, Bang Université de Montréal Mila Montréal Canada Microsoft Research Montréal Canada
Embodied Instruction Following (EIF) is crucial for understanding natural language in a practical context, requiring agents to follow verbal instructions for complex tasks. Traditionally, EIF relies heavily on expert ... 详细信息
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