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Machine translation = 20th China Conference, CCMT 2024, Xiamen, China, November 8-10, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine translation/ edited by Zhongjun He, Yidong Chen.
其他題名:	20th China Conference, CCMT 2024, Xiamen, China, November 8-10, 2024 : proceedings /
其他題名:	CCMT 2024
其他作者:	He, Zhongjun.
團體作者:	CCMT (Conference)
出版者:	Singapore :Springer Nature Singapore : : 2025.,
面頁冊數:	xiv, 176 p. :ill. (some col.), digital ;24 cm.
內容註:	Robustness and Efficiency of Translation Models. -- A Data-Efficient Nearest-Neighbor Language Model via Lightweight Nets. -- Extend Adversarial Policy Against Neural Machine Translation via Unknown Token. -- Low-resource Machine Translation. -- Evaluating the Translation Performance of Multilingual Large Language Models: a Case Study on Southeast Asian Language. -- Quality Estimation. -- Critical Error Detection based on Anchors Test. -- Large Language Modes for Machine Translation. -- Enhancing Machine Translation Across Multiple Domains and Languages with Large Language Models. -- Incorporating Terminology Knowledge into Large Language Model for Domain-specific Machine Translation. -- Multi-modal Translation. -- Joint Multi-modal Modeling for Speech-to-Text Translation as Multilingual Neural Machine Translation. -- Machine Translation Evaluation. -- CCMT2024 Tibetan-Chinese Machine Translation Evaluation Technical Report. -- HW-TSC's Submission to the CCMT 2024 Machine Translation Task. -- ISTIC's Neural Machine Translation Systems for CCMT' 2024. -- Lan-Bridge's Submission to CCMT 2024 Translation Evaluation Task. -- Technical Report of OPPO's Machine Translation Systems for CCMT 2024. -- Xihong's Submission to CCMT 2024: Human-in-the-Loop Data Augmentation for Low-Resource Tibetan-Chinese NMT.
Contained By:	Springer Nature eBook
標題:	Machine translating - Congresses. -
電子資源:	https://doi.org/10.1007/978-981-96-2292-4
ISBN:	9789819622924

Machine translation = 20th China Conference, CCMT 2024, Xiamen, China, November 8-10, 2024 : proceedings /
Machine translation20th China Conference, CCMT 2024, Xiamen, China, November 8-10, 2024 : proceedings /[electronic resource] :CCMT 2024edited by Zhongjun He, Yidong Chen. - Singapore :Springer Nature Singapore :2025. - xiv, 176 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,23651865-0937 ;. - Communications in computer and information science ;2365..

Robustness and Efficiency of Translation Models. -- A Data-Efficient Nearest-Neighbor Language Model via Lightweight Nets. -- Extend Adversarial Policy Against Neural Machine Translation via Unknown Token. -- Low-resource Machine Translation. -- Evaluating the Translation Performance of Multilingual Large Language Models: a Case Study on Southeast Asian Language. -- Quality Estimation. -- Critical Error Detection based on Anchors Test. -- Large Language Modes for Machine Translation. -- Enhancing Machine Translation Across Multiple Domains and Languages with Large Language Models. -- Incorporating Terminology Knowledge into Large Language Model for Domain-specific Machine Translation. -- Multi-modal Translation. -- Joint Multi-modal Modeling for Speech-to-Text Translation as Multilingual Neural Machine Translation. -- Machine Translation Evaluation. -- CCMT2024 Tibetan-Chinese Machine Translation Evaluation Technical Report. -- HW-TSC's Submission to the CCMT 2024 Machine Translation Task. -- ISTIC's Neural Machine Translation Systems for CCMT' 2024. -- Lan-Bridge's Submission to CCMT 2024 Translation Evaluation Task. -- Technical Report of OPPO's Machine Translation Systems for CCMT 2024. -- Xihong's Submission to CCMT 2024: Human-in-the-Loop Data Augmentation for Low-Resource Tibetan-Chinese NMT.

This book constitutes the refereed proceedings of the 20th China Conference on Machine Translation, CCMT 2024, which took place in Xiamen, China, during November 8-10, 2024. The 13 full papers included in this book were carefully reviewed and selected from 52 submissions. They were organized in topical sections as follows: robustness and efficiency of translation models; low-resource machine translation; quality estimation; large language modes for machine translation; multi-modal translation; and machine translation evaluation.

ISBN: 9789819622924

Standard No.: 10.1007/978-981-96-2292-4doiSubjects--Topical Terms:

1004837
Machine translating
--Congresses.

LC Class. No.: P308

Dewey Class. No.: 418.020285

Machine translation = 20th China Conference, CCMT 2024, Xiamen, China, November 8-10, 2024 : proceedings /
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