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The evolution of Neural Machine Translation (NMT) has been significantly influenced by six core challenges (Koehn and Knowles, 2017), which have acted as benchmarks for progress in this field.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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On early stopping in gradient descent learning
Yuan Yao, Lorenzo Rosasco, and Andrea Caponnetto. 2007 · 2007
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Statistical machine translation
Philipp Koehn. 2009 · 2009
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Interpolated backoff for factored translation models
Philipp Koehn and Barry Haddow. 2012 · 2012
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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Multidimensional quality metrics (mqm): A framework for declaring and describing translation quality metrics
Arle Lommel, Hans Uszkoreit, and Aljoscha Burchardt. 2014 · 2014
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Addressing the rare word problem in neural machine translation
Thang Luong, Ilya Sutskever, Quoc Le, Oriol Vinyals, and Wojciech Zaremba. 2015 · 2015
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, and et al. 2016 · 2016
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Overview of the IWSLT 2017 evaluation campaign
Mauro Cettolo, Marcello Federico, Luisa Bentivogli, Jan Niehues, Sebastian Stüker, Katsuhito Sudoh, Koichiro Yoshino, and Christian Federmann. 2017 · 2017
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Beam search strategies for neural machine translation
Markus Freitag and Yaser Al-Onaizan. 2017 · 2017
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Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
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Machine translation
Thierry Poibeau. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Exploiting cross-sentence context for neural machine translation
Longyue Wang, Zhaopeng Tu, Andy Way, and Qun Liu. 2017 · 2017
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A survey of domain adaptation for neural machine translation
Chenhui Chu and Rui Wang. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al. 2018 · 2018
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Jointly learning to align and translate with transformer models
Sarthak Garg, Stephan Peitz, Udhyakumar Nallasamy, and Matthias Paulik. 2019 · 2019
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On the word alignment from neural machine translation
Xintong Li, Guanlin Li, Lemao Liu, Max Meng, and Shuming Shi. 2019 · 2019
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On the relation between position information and sentence length in neural machine translation
Masato Neishi and Naoki Yoshinaga. 2019 · 2019
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Unsupervised domain clusters in pretrained language models
Roee Aharoni and Yoav Goldberg. 2020 · 2020
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Accurate word alignment induction from neural machine translation
Yun Chen, Yang Liu, Guanhua Chen, Xin Jiang, and Qun Liu. 2020 · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
Cited alongside, same era.
Go from the general to the particular: Multi-domain translation with domain transformation networks
Yong Wang, Longyue Wang, Shuming Shi, Victor OK Li, and Zhaopeng Tu. 2020 · 2020
Cited alongside, same era.
On the sub-layer functionalities of transformer decoder
Continual pre-training of large language models: How to (re) warm your model?
Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, and Timothée Lesort. 2023 · 2023
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ParroT: Translating during chat using large language models tuned with human translation and feedback
Wenxiang Jiao, Jen-tse Huang, Wenxuan Wang, Zhiwei He, Tian Liang, Xing Wang, Shuming Shi, and Zhaopeng Tu. 2023 · 2023
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Squeezellm: Dense-and-sparse quantization
Sehoon Kim, Coleman Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W Mahoney, and Kurt Keutzer. 2023 · 2023
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Compressing context to enhance inference efficiency of large language models
Yucheng Li, Bo Dong, Frank Guerin, and Chenghua Lin. 2023 · 2023
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Awq: Activation-aware weight quantization for llm compression and acceleration
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Yilin Yang, Longyue Wang, Shuming Shi, Prasad Tadepalli, Stefan Lee, and Zhaopeng Tu. 2020 · 2020
Cited alongside, same era.
End-to-end neural word alignment outperforms GIZA++
Thomas Zenkel, Joern Wuebker, and John DeNero. 2020 · 2020
Cited alongside, same era.
Measuring and improving faithfulness of attention in neural machine translation
Pooya Moradi, Nishant Kambhatla, and Anoop Sarkar. 2021 · 2021
Cited alongside, same era.
Context-aware self-attention networks for natural language processing
Baosong Yang, Longyue Wang, Derek F Wong, Shuming Shi, and Zhaopeng Tu. 2021 · 2021
Cited alongside, same era.
Continual pre-training mitigates forgetting in language and vision
Andrea Cossu, Tinne Tuytelaars, Antonio Carta, Lucia Passaro, Vincenzo Lomonaco, and Davide Bacciu. 2022 · 2022
Cited alongside, same era.
Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale
Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Cited alongside, same era.
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, and Song Han. 2023 · 2023
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G-eval: NLG evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
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New trends in machine translation using large language models: Case examples with chatgpt
Chenyang Lyu, Jitao Xu, and Longyue Wang. 2023 · 2023
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Gpteval: A survey on assessments of chatgpt and gpt-4
Rui Mao, Guanyi Chen, Xulang Zhang, Frank Guerin, and Erik Cambria. 2023 · 2023
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OpenAI. 2023 · 2023
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Rethinking the exploitation of monolingual data for low-resource neural machine translation
Jianhui Pang, Derek Fai Wong, Dayiheng Liu, Jun Xie, Baosong Yang, Yu Wan, and Lidia Sam Chao. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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Label words are anchors: An information flow perspective for understanding in-context learning
Lean Wang, Lei Li, Damai Dai, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou, and Xu Sun. 2023a · 2023
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Document-level machine translation with large language models
Longyue Wang, Chenyang Lyu, Tianbo Ji, Zhirui Zhang, Dian Yu, Shuming Shi, and Zhaopeng Tu. 2023b · 2023
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Findings of the WMT 2023 shared task on discourse-level literary translation: A fresh orb in the cosmos of LLMs
Longyue Wang, Zhaopeng Tu, Yan Gu, Siyou Liu, Dian Yu, Qingsong Ma, Chenyang Lyu, Liting Zhou, Chao-Hong Liu, Yufeng Ma, Weiyu Chen, Yvette Graham, Bonnie Webber, Philipp Koehn, Andy Way, Yulin Yuan, and Shuming Shi. 2023c · 2023
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Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al. 2023 · 2023
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Tower: An open multilingual large language model for translation-related tasks
Duarte M. Alves, José Pombal, Nuno M. Guerreiro, Pedro H. Martins, João Alves, Amin Farajian, Ben Peters, Ricardo Rei, Patrick Fernandes, Sweta Agrawal, Pierre Colombo, José G. C. de Souza, and André F. T. Martins. 2024 · 2024
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MoNMT: Modularly leveraging monolingual and bilingual knowledge for neural machine translation
Jianhui Pang, Baosong Yang, Derek F. Wong, Dayiheng Liu, Xiangpeng Wei, Jun Xie, and Lidia S. Chao. 2024a · 2024
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Anchor-based large language models
Jianhui Pang, Fanghua Ye, Derek Wong, Xin He, Wanshun Chen, and Longyue Wang. 2024b · 2024
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Multilingual large language model: A survey of resources, taxonomy and frontiers
Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, and Philip S Yu. 2024 · 2024
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An Yang, Baosong Yang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Zhou, Chengpeng Li, Chengyuan Li, Dayiheng Liu, Fei Huang, et al. 2024 · 2024
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Multilingual machine translation with large language models: Empirical results and analysis
Wenhao Zhu, Hongyi Liu, Qingxiu Dong, Jingjing Xu, Shujian Huang, Lingpeng Kong, Jiajun Chen, and Lei Li. 2024 · 2024
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