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Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02975786 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2020, 46 (4), pp.847-897 ; https://direct.mit.edu/coli/article/46/4/847/97326/Multi-SimLex-A-Large-Scale-Evaluation-of (2020)
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Towards zero-shot language modeling ...
Ponti, Edoardo; Vulić, I; Cotterell, R. - : Apollo - University of Cambridge Repository, 2020
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Multidirectional Associative Optimization of Function-Specific Word Representations ...
Gerz, Daniela; Vulic, Ivan; Rei, Marek. - : Apollo - University of Cambridge Repository, 2020
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XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
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Emergent Communication Pretraining for Few-Shot Machine Translation ...
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Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2020
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Emergent Communication Pretraining for Few-Shot Machine Translation ...
Li, Yaoyiran; Ponti, Edoardo; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2020
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XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
Ponti, Edoardo; Glavaš, Goran; Majewska, Olga; Liu, Qianchu; Vulic, Ivan; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2020
Abstract: In order to simulate human language capacity, natural language processing systems must be able to reason about the dynamics of everyday situations, including their possible causes and effects. Moreover, they should be able to generalise the acquired world knowledge to new languages, modulo cultural differences. Advances in machine reasoning and cross-lingual transfer depend on the availability of challenging evaluation benchmarks. Motivated by both demands, we introduce Cross-lingual Choice of Plausible Alternatives (XCOPA), a typologically diverse multilingual dataset for causal commonsense reasoning in 11 languages, which includes resource-poor languages like Eastern Apurímac Quechua and Haitian Creole. We evaluate a range of state-of-the-art models on this novel dataset, revealing that the performance of current methods based on multilingual pretraining and zero-shot fine-tuning falls short compared to translation-based transfer. Finally, we propose strategies to adapt multilingual models to out-of-sample ...
URL: https://www.repository.cam.ac.uk/handle/1810/315102
https://dx.doi.org/10.17863/cam.62209
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9
Emergent Communication Pretraining for Few-Shot Machine Translation ...
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10
Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
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11
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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12
Verb Knowledge Injection for Multilingual Event Processing ...
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13
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
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14
Probing Pretrained Language Models for Lexical Semantics ...
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15
The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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18
Cross-lingual semantic specialization via lexical relation induction ...
Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020
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Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization ...
Ponti, Edoardo; Vulić, I; Glavaš, G. - : Apollo - University of Cambridge Repository, 2020
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20
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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