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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 Hits 1 – 7 of 7 1 MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ... Pfeiffer, Jonas; Vulić, Ivan; Gurevych, Iryna; Ruder, Sebastian. - : arXiv, 2020 Abstract: The main goal behind state-of-the-art pre-trained multilingual models such as multilingual BERT and XLM-R is enabling and bootstrapping NLP applications in low-resource languages through zero-shot or few-shot cross-lingual transfer. However, due to limited model capacity, their transfer performance is the weakest exactly on such low-resource languages and languages unseen during pre-training. We propose MAD-X, an adapter-based framework that enables high portability and parameter-efficient transfer to arbitrary tasks and languages by learning modular language and task representations. In addition, we introduce a novel invertible adapter architecture and a strong baseline method for adapting a pre-trained multilingual model to a new language. MAD-X outperforms the state of the art in cross-lingual transfer across a representative set of typologically diverse languages on named entity recognition and causal commonsense reasoning, and achieves competitive results on question answering. Our code and adapters are ... : EMNLP 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2005.00052 https://dx.doi.org/10.48550/arxiv.2005.00052 BASE Hide details 2 How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ... Rust, Phillip; Pfeiffer, Jonas; Vulić, Ivan. - : arXiv, 2020 BASE Show details 3 UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ... Pfeiffer, Jonas; Vulić, Ivan; Gurevych, Iryna. - : arXiv, 2020 BASE Show details 4 MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ... Pfeiffer, Jonas; Vulic, Ivan; Gurevych, Iryna. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 5 MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer Vulic, Ivan; Pfeiffer, Jonas; Ruder, Sebastian. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 BASE Show details 6 AdapterHub: A Framework for Adapting Transformers Pfeiffer, Jonas; Ruckle, Andreas; Poth, Clifton. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP 2020), 2020 BASE Show details 7 Specializing distributional vectors of all words for lexical entailment Ponti, Edoardo Maria; Kamath, Aishwarya; Pfeiffer, Jonas. - : Association for Computational Linguistics, 2019 BASE Show details

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