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Sensitising language models (LMs) to external context helps them to more effectively capture the speaking patterns of individuals with specific characteristics or in particular environments.
Methods and metrics for cold-start recommendations
Andrew I. Schein, Alexandrin Popescul, Lyle H. Ungar, and David M. Pennock. 2002 · 2002
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Speech community: Reflections upon communication
Trudy Milburn. 2004 · 2004
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Chameleons in imagined conversations: A new approach to understanding coordination of linguistic style in dialogs
Cristian Danescu-Niculescu-Mizil and Lillian Lee. 2011 · 2011
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Enriching cold start personalized language model using social network information
Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo, and Shou-De Lin. 2014 · 2014
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Scientific research must take gender into account
Londa Schiebinger. 2014 · 2014
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Demographic factors improve classification performance
Dirk Hovy. 2015 · 2015
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Cross-lingual syntactic variation over age and gender
Anders Johannsen, Dirk Hovy, and Anders Søgaard. 2015 · 2015
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Controlling politeness in neural machine translation via side constraints
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Human centered NLP with user-factor adaptation
Veronica Lynn, Youngseo Son, Vivek Kulkarni, Niranjan Balasubramanian, and H. Andrew Schwartz. 2017 · 2017
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Evaluating discourse phenomena in neural machine translation
Rachel Bawden, Rico Sennrich, Alexandra Birch, and Barry Haddow. 2018 · 2018
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OpenSubtitles2018: Statistical rescoring of sentence alignments in large, noisy parallel corpora
Pierre Lison, Jörg Tiedemann, and Milen Kouylekov. 2018 · 2018
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Extreme adaptation for personalized neural machine translation
Paul Michel and Graham Neubig. 2018 · 2018
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A large-scale test set for the evaluation of context-aware pronoun translation in neural machine translation
Mathias Müller, Annette Rios, Elena Voita, and Rico Sennrich. 2018 · 2018
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Simple fusion: Return of the language model
Felix Stahlberg, James Cross, and Veselin Stoyanov. 2018 · 2018
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CTRL: A conditional transformer language model for controllable generation
Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, Caiming Xiong, and Richard Socher. 2019 · 2019
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When a good translation is wrong in context: Context-aware machine translation improves on deixis, ellipsis, and lexical cohesion
Elena Voita, Rico Sennrich, and Ivan Titov. 2019 · 2019
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Refocusing on relevance: Personalization in NLG
Shiran Dudy, Steven Bedrick, and Bonnie Webber. 2021 · 2021
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A context-aware language model to improve the speech recognition in air traffic control
Dongyue Guo, Zichen Zhang, Peng Fan, Jianwei Zhang, and Bo Yang. 2021 · 2021
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Context-aware decoder for neural machine translation using a target-side document-level language model
Amane Sugiyama and Naoki Yoshinaga. 2021 · 2021
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UserIdentifier: Implicit user representations for simple and effective personalized sentiment analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, and Dimitrios Dimitriadis. 2022 · 2022
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CUE vectors: Modular training of language models conditioned on diverse contextual signals
Scott Novotney, Sreeparna Mukherjee, Zeeshan Ahmed, and Andreas Stolcke. 2022 · 2022
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Automatic generation of personalized comment based on user profile
Wenhuan Zeng, Abulikemu Abuduweili, Lei Li, and Pengcheng Yang. 2019 · 2019
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On the evaluation of machine translation systems trained with back-translation
Sergey Edunov, Myle Ott, Marc’Aurelio Ranzato, and Michael Auli. 2020 · 2020
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Returning the N to NLP: Towards contextually personalized classification models
Lucie Flek. 2020 · 2020
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Evaluating approaches to personalizing language models
Milton King and Paul Cook. 2020 · 2020
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Document-level neural MT: A systematic comparison
António Lopes, M. Amin Farajian, Rachel Bawden, Michael Zhang, and André F. T. Martins. 2020 · 2020
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Compositional demographic word embeddings
Charles Welch, Jonathan K. Kummerfeld, Verónica Pérez-Rosas, and Rada Mihalcea. 2020 · 2020
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Controlling extra-textual attributes about dialogue participants: A case study of English-to-Polish neural machine translation
Sebastian T. Vincent, Loïc Barrault, and Carolina Scarton. 2022b
Cited in the paper.
Controlling formality in low-resource NMT with domain adaptation and re-ranking: SLT-CDT-UoS at IWSLT2022
Sebastian Vincent, Loïc Barrault, and Carolina Scarton. 2022a · 2022
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Leveraging similar users for personalized language modeling with limited data
Charles Welch, Chenxi Gu, Jonathan K. Kummerfeld, Veronica Perez-Rosas, and Rada Mihalcea. 2022 · 2022
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Escaping the sentence-level paradigm in machine translation
Matt Post and Marcin Junczys-Dowmunt. 2023 · 2023
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Context-Based Personalisation in Neural Machine Translation of Dialogue
Sebastian Vincent. 2023 · 2023
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MTCue: Learning zero-shot control of extra-textual attributes by leveraging unstructured context in neural machine translation
Sebastian Vincent, Robert Flynn, and Carolina Scarton. 2023 · 2023
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