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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 – 19 of 19 1 Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ... Litschko, Robert; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2022 BASE Show details 2 Geographic Adaptation of Pretrained Language Models ... Hofmann, Valentin; Glavaš, Goran; Ljubešić, Nikola. - : arXiv, 2022 BASE Show details 3 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 4 On Cross-Lingual Retrieval with Multilingual Text Encoders ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 5 Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ... Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : arXiv, 2021 BASE Show details 6 AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ... Lauscher, Anne; Takieddin, Rafik; Ponzetto, Simone Paolo. - : arXiv, 2020 BASE Show details 7 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ... Ponti, Edoardo Maria; Glavaš, Goran; Majewska, Olga. - : arXiv, 2020 BASE Show details 8 On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ... Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : arXiv, 2020 BASE Show details 9 Orthogonal Language and Task Adapters in Zero-Shot Cross-Lingual Transfer ... Vidoni, Marko; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2020 BASE Show details 10 From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ... Lauscher, Anne; Ravishankar, Vinit; Vulić, Ivan. - : arXiv, 2020 BASE Show details 11 Verb Knowledge Injection for Multilingual Event Processing ... Majewska, Olga; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2020 BASE Show details 12 Probing Pretrained Language Models for Lexical Semantics ... Vulić, Ivan; Ponti, Edoardo Maria; Litschko, Robert. - : arXiv, 2020 BASE Show details 13 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : arXiv, 2019 BASE Show details 14 Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ... Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : arXiv, 2019 BASE Show details 15 How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions ... Glavas, Goran; Litschko, Robert; Ruder, Sebastian. - : arXiv, 2019 BASE Show details 16 Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only ... Litschko, Robert; Glavaš, Goran; Ponzetto, Simone Paolo. - : arXiv, 2018 BASE Show details 17 Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization ... Ponti, Edoardo Maria; Vulić, Ivan; Glavaš, Goran; Mrkšić, Nikola; Korhonen, Anna. - : arXiv, 2018 Abstract: Semantic specialization is the process of fine-tuning pre-trained distributional word vectors using external lexical knowledge (e.g., WordNet) to accentuate a particular semantic relation in the specialized vector space. While post-processing specialization methods are applicable to arbitrary distributional vectors, they are limited to updating only the vectors of words occurring in external lexicons (i.e., seen words), leaving the vectors of all other words unchanged. We propose a novel approach to specializing the full distributional vocabulary. Our adversarial post-specialization method propagates the external lexical knowledge to the full distributional space. We exploit words seen in the resources as training examples for learning a global specialization function. This function is learned by combining a standard L2-distance loss with an adversarial loss: the adversarial component produces more realistic output vectors. We show the effectiveness and robustness of the proposed method across three ... : Accepted at EMNLP 2018 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1809.04163 https://arxiv.org/abs/1809.04163 BASE Hide details 18 Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ... Vulić, Ivan; Glavaš, Goran; Mrkšić, Nikola. - : arXiv, 2018 BASE Show details 19 A Resource-Light Method for Cross-Lingual Semantic Textual Similarity ... Glavaš, Goran; Franco-Salvador, Marc; Ponzetto, Simone Paolo. - : arXiv, 2018 BASE Show details

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