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Multilingual and Cross-Lingual Intent Detection from Spoken Data ...
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Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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Modelling Latent Translations for Cross-Lingual Transfer ...
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Prix-LM: Pretraining for Multilingual Knowledge Base Construction ...
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Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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On Cross-Lingual Retrieval with Multilingual Text Encoders ...
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MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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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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RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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Parameter space factorization for zero-shot learning across tasks and languages ...
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MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
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How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
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