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A High-Quality Multilingual Dataset for Structured Documentation Translation ...
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Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ...
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Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ...
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Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering ...
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Multilingual Extractive Reading Comprehension by Runtime Machine Translation ...
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Adaptive Joint Learning of Compositional and Non-Compositional Phrase Embeddings ...
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A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks ...
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Abstract:
Transfer and multi-task learning have traditionally focused on either a single source-target pair or very few, similar tasks. Ideally, the linguistic levels of morphology, syntax and semantics would benefit each other by being trained in a single model. We introduce a joint many-task model together with a strategy for successively growing its depth to solve increasingly complex tasks. Higher layers include shortcut connections to lower-level task predictions to reflect linguistic hierarchies. We use a simple regularization term to allow for optimizing all model weights to improve one task's loss without exhibiting catastrophic interference of the other tasks. Our single end-to-end model obtains state-of-the-art or competitive results on five different tasks from tagging, parsing, relatedness, and entailment tasks. ... : Accepted as a full paper at the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017) ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1611.01587 https://arxiv.org/abs/1611.01587
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Task-Oriented Learning of Word Embeddings for Semantic Relation Classification ...
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