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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 4 Hits 41 – 60 of 75 41 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.423, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 42 Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction Karan, Mladen; Vulic, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020 BASE Show details 43 Emergent Communication Pretraining for Few-Shot Machine Translation Vulic, Ivan; Ponti, Edoardo; Korhonen, Anna; Li, Yaoyiran. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.416, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 Abstract: While state-of-the-art models that rely upon massively multilingual pretrained encoders achieve sample efficiency in downstream applications, they still require abundant amounts of unlabelled text. Nevertheless, most of the world’s languages lack such resources. Hence, we investigate a more radical form of unsupervised knowledge transfer in the absence of linguistic data. In particular, for the first time we pretrain neural networks via emergent communication from referential games. Our key assumption is that grounding communication on images—as a crude approximation of real-world environments—inductively biases the model towards learning natural languages. On the one hand, we show that this substantially benefits machine translation in few-shot settings. On the other hand, this also provides an extrinsic evaluation protocol to probe the properties of emergent languages ex vitro. Intuitively, the closer they are to natural languages, the higher the gains from pretraining on them should be. For instance, in this work we measure the influence of communication success and maximum sequence length on downstream performances. Finally, we introduce a customised adapter layer and annealing strategies for the regulariser of maximum-a-posteriori inference during fine-tuning. These turn out to be crucial to facilitate knowledge transfer and prevent catastrophic forgetting. Compared to a recurrent baseline, our method yields gains of 59.0%∼147.6% in BLEU score with only 500 NMT training instances and 65.1%∼196.7% with 1, 000 NMT training instances across four language pairs. These proof-of-concept results reveal the potential of emergent communication pretraining for both natural language processing tasks in resource-poor settings and extrinsic evaluation of artificial languages. URL: https://doi.org/10.17863/CAM.62217 https://www.repository.cam.ac.uk/handle/1810/315110 BASE Hide details 44 Multidirectional Associative Optimization of Function-Specific Word Representations Gerz, Daniela; Vulic, Ivan; Rei, Marek. - : Association for Computational Linguistics, 2020. : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020 BASE Show details 45 Specializing unsupervised pretraining models for word-level semantic similarity Ponti, Edoardo Maria; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, ACL, 2020 BASE Show details 46 Classification-based self-learning for weakly supervised bilingual lexicon induction Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020 BASE Show details 47 Probing pretrained language models for lexical semantics Vulić, Ivan; Korhonen, Anna; Litschko, Robert. - : Association for Computational Linguistics, 2020 BASE Show details 48 XCOPA: A multilingual dataset for causal commonsense reasoning Ponti, Edoardo Maria; Majewska, Olga; Liu, Qianchu. - : Association for Computational Linguistics, 2020 BASE Show details 49 Improving bilingual lexicon induction with unsupervised post-processing of monolingual word vector spaces Glavaš, Goran; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, 2020 BASE Show details 50 SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020 BASE Show details 51 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo Maria; O’Horan, Helen; Berzak, Yevgeni... In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02425462 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (3), pp.559-601. ⟨10.1162/coli_a_00357⟩ ; https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00357 (2019) BASE Show details 52 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : arXiv, 2019 BASE Show details 53 Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ... Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : arXiv, 2019 BASE Show details 54 Multilingual and cross-lingual graded lexical entailment Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019 BASE Show details 55 How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019 BASE Show details 56 Cross-lingual semantic specialization via lexical relation induction Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019 BASE Show details 57 Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019 BASE Show details 58 Informing unsupervised pretraining with external linguistic knowledge Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : Cornell University, 2019 BASE Show details 59 Do we really need fully unsupervised cross-lingual embeddings? Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : Association for Computational Linguistics, 2019 BASE Show details 60 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo Maria; O’Horan, Helen; Berzak, Yevgeni... In: Computational Linguistics, Vol 45, Iss 3, Pp 559-601 (2019) (2019) BASE Show details Page: 1 2 3 4

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