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Delving Deeper into Cross-lingual Visual Question Answering ...
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IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages ...
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Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation ...
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Abstract:
Recent work on multilingual AMR-to-text generation has exclusively focused on data augmentation strategies that utilize silver AMR. However, this assumes a high quality of generated AMRs, potentially limiting the transferability to the target task. In this paper, we investigate different techniques for automatically generating AMR annotations, where we aim to study which source of information yields better multilingual results. Our models trained on gold AMR with silver (machine translated) sentences outperform approaches which leverage generated silver AMR. We find that combining both complementary sources of information further improves multilingual AMR-to-text generation. Our models surpass the previous state of the art for German, Italian, Spanish, and Chinese by a large margin. ... : Accepted as a conference paper to EMNLP 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2109.03808 https://dx.doi.org/10.48550/arxiv.2109.03808
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Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation ...
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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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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
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How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
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UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer
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AdapterHub: A Framework for Adapting Transformers
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Pfeiffer, Jonas; Ruckle, Andreas; Poth, Clifton. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP 2020), 2020
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Specialising Distributional Vectors of All Words for Lexical Entailment ...
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Specializing distributional vectors of all words for lexical entailment
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A neural autoencoder approach for document ranking and query refinement in pharmacogenomic information retrieval
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