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Delving Deeper into Cross-lingual Visual Question Answering ...
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Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation ...
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Improving Word Translation via Two-Stage Contrastive Learning ...
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Abstract:
Word translation or bilingual lexicon induction (BLI) is a key cross-lingual task, aiming to bridge the lexical gap between different languages. In this work, we propose a robust and effective two-stage contrastive learning framework for the BLI task. At Stage C1, we propose to refine standard cross-lingual linear maps between static word embeddings (WEs) via a contrastive learning objective; we also show how to integrate it into the self-learning procedure for even more refined cross-lingual maps. In Stage C2, we conduct BLI-oriented contrastive fine-tuning of mBERT, unlocking its word translation capability. We also show that static WEs induced from the `C2-tuned' mBERT complement static WEs from Stage C1. Comprehensive experiments on standard BLI datasets for diverse languages and different experimental setups demonstrate substantial gains achieved by our framework. While the BLI method from Stage C1 already yields substantial gains over all state-of-the-art BLI methods in our comparison, even stronger ... : ACL 2022 Main ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR; Machine Learning cs.LG
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URL: https://arxiv.org/abs/2203.08307 https://dx.doi.org/10.48550/arxiv.2203.08307
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Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ...
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MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained 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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Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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Semantic Data Set Construction from Human Clustering and Spatial Arrangement ...
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Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
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Context vs Target Word: Quantifying Biases in Lexical Semantic Datasets ...
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AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
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Parameter space factorization for zero-shot learning across tasks and languages
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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