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On Cross-Lingual Retrieval with Multilingual Text Encoders ...
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Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
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Abstract:
Pretrained multilingual text encoders based on neural Transformer architectures, such as multilingual BERT (mBERT) and XLM, have achieved strong performance on a myriad of language understanding tasks. Consequently, they have been adopted as a go-to paradigm for multilingual and cross-lingual representation learning and transfer, rendering cross-lingual word embeddings (CLWEs) effectively obsolete. However, questions remain to which extent this finding generalizes 1) to unsupervised settings and 2) for ad-hoc cross-lingual IR (CLIR) tasks. Therefore, in this work we present a systematic empirical study focused on the suitability of the state-of-the-art multilingual encoders for cross-lingual document and sentence retrieval tasks across a large number of language pairs. In contrast to supervised language understanding, our results indicate that for unsupervised document-level CLIR -- a setup with no relevance judgments for IR-specific fine-tuning -- pretrained encoders fail to significantly outperform models ... : accepted at ECIR'21 (preprint) ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; H.3.3; I.2.7; Information Retrieval cs.IR
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URL: https://dx.doi.org/10.48550/arxiv.2101.08370 https://arxiv.org/abs/2101.08370
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Come hither or go away? Recognising pre-electoral coalition signals in the news ...
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Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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Come hither or go away? Recognising pre-electoral coalition signals in the news
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AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ...
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Word Sense Disambiguation for 158 Languages using Word Embeddings Only ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment
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Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena. - : International Committee for Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.semeval-1.2, 2020. : Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020), 2020
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A Twitter Political Corpus of the 2019 10N Spanish Election
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AraWEAT: Multidimensional analysis of biases in Arabic word embeddings
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SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment
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Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ...
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Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ...
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HHMM at SemEval-2019 Task 2: Unsupervised frame induction using contextualized word embeddings
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Policy preference detection in parliamentary debate motions
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Watset: Local-global graph clustering with applications in sense and frame induction
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