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Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language ...
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On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions ...
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Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ...
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Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ...
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From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding ...
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On the Difficulty of Translating Free-Order Case-Marking Languages ...
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UDapter: Language Adaptation for Truly Universal Dependency Parsing ...
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FiSSA at SemEval-2020 Task 9: Fine-tuned For Feelings ...
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Abstract:
In this paper, we present our approach for sentiment classification on Spanish-English code-mixed social media data in the SemEval-2020 Task 9. We investigate performance of various pre-trained Transformer models by using different fine-tuning strategies. We explore both monolingual and multilingual models with the standard fine-tuning method. Additionally, we propose a custom model that we fine-tune in two steps: once with a language modeling objective, and once with a task-specific objective. Although two-step fine-tuning improves sentiment classification performance over the base model, the large multilingual XLM-RoBERTa model achieves best weighted F1-score with 0.537 on development data and 0.739 on test data. With this score, our team jupitter placed tenth overall in the competition. ... : In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval-2020), Barcelona, Spain, December. Association for Computational Linguistics ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2007.12544 https://dx.doi.org/10.48550/arxiv.2007.12544
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Incorporating word embeddings in unsupervised morphological segmentation
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In: 2020 ; 1 ; 21 (2020)
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A Trie-Structured Bayesian Model for Unsupervised Morphological Segmentation ...
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Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets ...
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