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A Quantitative and Qualitative Analysis of Schizophrenia Language ...
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Towards Responsible Natural Language Annotation for the Varieties of Arabic ...
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Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation ...
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AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization ...
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Detecting Hallucinated Content in Conditional Neural Sequence Generation ...
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Gender bias amplification during Speed-Quality optimization in Neural Machine Translation ...
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Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ...
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Discrete Cosine Transform as Universal Sentence Encoder ...
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Discrete Cosine Transform as Universal Sentence Encoder ...
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Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages ...
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DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking ...
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Mutlitask Learning for Cross-Lingual Transfer of Semantic Dependencies ...
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Abstract:
We describe a method for developing broad-coverage semantic dependency parsers for languages for which no semantically annotated resource is available. We leverage a multitask learning framework coupled with an annotation projection method. We transfer supervised semantic dependency parse annotations from a rich-resource language to a low-resource language through parallel data, and train a semantic parser on projected data. We make use of supervised syntactic parsing as an auxiliary task in a multitask learning framework, and show that with different multitask learning settings, we consistently improve over the single-task baseline. In the setting in which English is the source, and Czech is the target language, our best multitask model improves the labeled F1 score over the single-task baseline by 1.8 in the in-domain SemEval data (Oepen et al., 2015), as well as 2.5 in the out-of-domain test set. Moreover, we observe that syntactic and semantic dependency direction match is an important factor in ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2004.14961 https://dx.doi.org/10.48550/arxiv.2004.14961
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Overview for the Second Shared Task on Language Identification in Code-Switched Data ...
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Creating a Large Multi-Layered Representational Repository of Linguistic Code Switched Arabic Data ...
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Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues ...
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Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task ...
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