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Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
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42 |
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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43 |
Verb Knowledge Injection for Multilingual Event Processing ...
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Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
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Probing Pretrained Language Models for Lexical Semantics ...
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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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49 |
Cross-lingual semantic specialization via lexical relation induction ...
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Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization ...
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51 |
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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Do we really need fully unsupervised cross-lingual embeddings? ...
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54 |
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
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55 |
Probing Pretrained Language Models for Lexical Semantics ...
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56 |
Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction ...
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57 |
On the relation between linguistic typology and (limitations of) multilingual language modeling ...
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58 |
Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces ...
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The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures ...
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Abstract:
Performance in cross-lingual NLP tasks is impacted by the (dis)similarity of languages at hand: e.g., previous work has suggested there is a connection between the expected success of bilingual lexicon induction (BLI) and the assumption of (approximate) isomorphism between monolingual embedding spaces. In this work we present a large-scale study focused on the correlations between monolingual embedding space similarity and task performance, covering thousands of language pairs and four different tasks: BLI, parsing, POS tagging and MT. We hypothesize that statistics of the spectrum of each monolingual embedding space indicate how well they can be aligned. We then introduce several isomorphism measures between two embedding spaces, based on the relevant statistics of their individual spectra. We empirically show that 1) language similarity scores derived from such spectral isomorphism measures are strongly associated with performance observed in different cross-lingual tasks, and 2) our spectral-based ...
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URL: https://www.repository.cam.ac.uk/handle/1810/315101 https://dx.doi.org/10.17863/cam.62208
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Spatial multi-arrangement for clustering and multi-way similarity dataset construction ...
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