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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 22 1 XTREME-S: Evaluating Cross-lingual Speech Representations ... Conneau, Alexis; Bapna, Ankur; Zhang, Yu. - : arXiv, 2022 BASE Show details 2 Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation ... Cheng, Yong; Bapna, Ankur; Firat, Orhan. - : arXiv, 2022 BASE Show details 3 Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning ... Siddhant, Aditya; Bapna, Ankur; Firat, Orhan. - : arXiv, 2022 BASE Show details 4 mSLAM: Massively multilingual joint pre-training for speech and text ... Bapna, Ankur; Cherry, Colin; Zhang, Yu. - : arXiv, 2022 BASE Show details 5 Examining Scaling and Transfer of Language Model Architectures for Machine Translation ... Zhang, Biao; Ghorbani, Behrooz; Bapna, Ankur. - : arXiv, 2022 BASE Show details 6 MAESTRO: Matched Speech Text Representations through Modality Matching ... Chen, Zhehuai; Zhang, Yu; Rosenberg, Andrew. - : arXiv, 2022 BASE Show details 7 Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets Caswell, Isaac; Kreutzer, Julia; Wang, Lisa... In: https://hal.inria.fr/hal-03177623 ; 2021 (2021) BASE Show details 8 Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets ... Kreutzer, Julia; Caswell, Isaac; Wang, Lisa. - : arXiv, 2021 BASE Show details 9 Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents ... Zhang, Biao; Bapna, Ankur; Johnson, Melvin. - : arXiv, 2021 BASE Show details 10 Joint Unsupervised and Supervised Training for Multilingual ASR ... Bai, Junwen; Li, Bo; Zhang, Yu. - : arXiv, 2021 BASE Show details 11 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation ... Zhang, Biao; Bapna, Ankur; Sennrich, Rico. - : ICLR, 2021 BASE Show details 12 Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference ... Kudugunta, Sneha; Huang, Yanping; Bapna, Ankur. - : arXiv, 2021 BASE Show details 13 Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bapna, Ankur; Firat, Orhan. - : Underline Science Inc., 2021 BASE Show details 14 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation Zhang, Biao; Bapna, Ankur; Sennrich, Rico; Firat, Orhan In: Zhang, Biao; Bapna, Ankur; Sennrich, Rico; Firat, Orhan (2021). Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation. In: International Conference on Learning Representations, Virtual, 3 May 2021 - 7 May 2021, ICLR. (2021) Abstract: Using a mix of shared and language-specific (LS) parameters has shown promise in multilingual neural machine translation (MNMT), but the question of when and where LS capacity matters most is still under-studied. We offer such a study by proposing conditional language-specific routing (CLSR). CLSR employs hard binary gates conditioned on token representations to dynamically select LS or shared paths. By manipulating these gates, it can schedule LS capacity across sub-layers in MNMT subject to the guidance of translation signals and budget constraints. Moreover, CLSR can easily scale up to massively multilingual settings. Experiments with Transformer on OPUS-100 and WMT datasets show that: 1) MNMT is sensitive to both the amount and the position of LS modeling: distributing 10%-30% LS computation to the top and/or bottom encoder/decoder layers delivers the best performance; and 2) one-to-many translation benefits more from CLSR compared to many-to-one translation, particularly with unbalanced training data. Our study further verifies the trade-off between the shared capacity and LS capacity for multilingual translation. We corroborate our analysis by confirming the soundness of our findings as foundation of our improved multilingual Transformers. Source code and models are available at https://github.com/bzhangGo/zero/tree/iclr2021_clsr. Code Of Ethics: I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics One-sentence Summary: We investigate and improve parameter-sharing strategies in multilingual Transformers by utilizing conditional computation. Keyword: 000 Computer science; 410 Linguistics; Institute of Computational Linguistics; knowledge & systems URL: https://doi.org/10.5167/uzh-208876 https://openreview.net/forum?id=Wj4ODo0uyCF https://www.zora.uzh.ch/id/eprint/208876/ https://www.zora.uzh.ch/id/eprint/208876/1/share_or_not_learning_to_sched.pdf BASE Hide details 15 Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation ... Siddhant, Aditya; Bapna, Ankur; Cao, Yuan. - : arXiv, 2020 BASE Show details 16 Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus ... Caswell, Isaac; Breiner, Theresa; van Esch, Daan. - : arXiv, 2020 BASE Show details 17 Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation ... Siddhant, Aditya; Johnson, Melvin; Tsai, Henry. - : arXiv, 2019 BASE Show details 18 Investigating Multilingual NMT Representations at Scale ... Kudugunta, Sneha Reddy; Bapna, Ankur; Caswell, Isaac. - : arXiv, 2019 BASE Show details 19 Simple, Scalable Adaptation for Neural Machine Translation ... Bapna, Ankur; Arivazhagan, Naveen; Firat, Orhan. - : arXiv, 2019 BASE Show details 20 Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges ... Arivazhagan, Naveen; Bapna, Ankur; Firat, Orhan. - : arXiv, 2019 BASE Show details Page: 1 2

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