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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 3 Hits 1 – 20 of 45 1 Delving Deeper into Cross-lingual Visual Question Answering ... Liu, Chen; Pfeiffer, Jonas; Korhonen, Anna. - : arXiv, 2022 BASE Show details 2 Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation ... Majewska, Olga; Razumovskaia, Evgeniia; Ponti, Edoardo Maria. - : arXiv, 2022 BASE Show details 3 Improving Word Translation via Two-Stage Contrastive Learning ... Li, Yaoyiran; Liu, Fangyu; Collier, Nigel. - : arXiv, 2022 BASE Show details 4 Towards Zero-shot Language Modeling ... Ponti, Edoardo Maria; Vulić, Ivan; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 5 Multilingual and Cross-Lingual Intent Detection from Spoken Data ... Gerz, Daniela; Su, Pei-Hao; Kusztos, Razvan. - : arXiv, 2021 BASE Show details 6 Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ... Razumovskaia, Evgeniia; Glavaš, Goran; Majewska, Olga. - : arXiv, 2021 BASE Show details 7 Modelling Latent Translations for Cross-Lingual Transfer ... Ponti, Edoardo Maria; Kreutzer, Julia; Vulić, Ivan. - : arXiv, 2021 BASE Show details 8 Prix-LM: Pretraining for Multilingual Knowledge Base Construction ... Zhou, Wenxuan; Liu, Fangyu; Vulić, Ivan. - : arXiv, 2021 BASE Show details 9 Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 10 xGQA: Cross-Lingual Visual Question Answering ... Pfeiffer, Jonas; Geigle, Gregor; Kamath, Aishwarya. - : arXiv, 2021 BASE Show details 11 On Cross-Lingual Retrieval with Multilingual Text Encoders ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 12 MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ... Liu, Qianchu; Liu, Fangyu; Collier, Nigel. - : arXiv, 2021 BASE Show details 13 Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 14 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... Liu, Qianchu; Ponti, Edoardo M.; McCarthy, Diana. - : arXiv, 2021 BASE Show details 15 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 16 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ... Ponti, Edoardo Maria; Glavaš, Goran; Majewska, Olga. - : arXiv, 2020 BASE Show details 17 Emergent Communication Pretraining for Few-Shot Machine Translation ... Li, Yaoyiran; Ponti, Edoardo M.; Vulić, Ivan. - : arXiv, 2020 BASE Show details 18 Orthogonal Language and Task Adapters in Zero-Shot Cross-Lingual Transfer ... Vidoni, Marko; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2020 BASE Show details 19 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 20 How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ... Rust, Phillip; Pfeiffer, Jonas; Vulić, Ivan. - : arXiv, 2020 BASE Show details Page: 1 2 3

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