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61
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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62
From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
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63
Verb Knowledge Injection for Multilingual Event Processing ...
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64
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
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65
Probing Pretrained Language Models for Lexical Semantics ...
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66
The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures ...
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67
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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68
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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69
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020
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70
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2020
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71
Non-Linear Instance-Based Cross-Lingual Mapping for Non-Isomorphic Embedding Spaces ...
Glavas, Goran; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2020
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72
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
Vulic, Ivan; Baker, Simon; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020
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73
Probing Pretrained Language Models for Lexical Semantics ...
Vulic, Ivan; Ponti, Edoardo; Litschko, Robert; Glavas, Goran; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2020
Abstract: The success of large pretrained language models (LMs) such as BERT and RoBERTa has sparked interest in probing their representations, in order to unveil what types of knowledge they implicitly capture. While prior research focused on morphosyntactic, semantic, and world knowledge, it remains unclear to which extent LMs also derive lexical type-level knowledge from words in context. In this work, we present a systematic empirical analysis across six typologically diverse languages and five different lexical tasks, addressing the following questions: 1) How do different lexical knowledge extraction strategies (monolingual versus multilingual source LM, out-of-context versus in-context encoding, inclusion of special tokens, and layer-wise averaging) impact performance? How consistent are the observed effects across tasks and languages? 2) Is lexical knowledge stored in few parameters, or is it scattered throughout the network? 3) How do these representations fare against traditional static word vectors in ...
URL: https://dx.doi.org/10.17863/cam.62212
https://www.repository.cam.ac.uk/handle/1810/315105
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74
Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction ...
Karan, Mladen; Vulic, Ivan; Korhonen, Anna. - : Apollo - University of Cambridge Repository, 2020
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75
Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces ...
Vulic, Ivan; Korhonen, Anna; Glavas, Goran. - : Apollo - University of Cambridge Repository, 2020
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76
The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures ...
Dubossarsky, Haim; Vulic, Ivan; Reichart, Roi. - : Apollo - University of Cambridge Repository, 2020
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77
Spatial multi-arrangement for clustering and multi-way similarity dataset construction ...
Majewska, Olga; McCarthy, D; Van Den Bosch, J. - : Apollo - University of Cambridge Repository, 2020
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78
Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces
Vulic, Ivan; Korhonen, Anna; Glavas, Goran. - : 5TH WORKSHOP ON REPRESENTATION LEARNING FOR NLP (REPL4NLP-2020), 2020
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79
The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures
Dubossarsky, Haim; Vulic, Ivan; Reichart, Roi. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020
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80
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity
Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.118, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020
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