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Negative language transfer in learner English: A new dataset ...
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Generative Imagination Elevates Machine Translation ...
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Abstract:
Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.457/ Abstract: There are common semantics shared across text and images. Given a sentence in a source language, whether depicting the visual scene helps translation into a target language? Existing multimodal neural machine translation methods (MNMT) require triplets of bilingual sentence - image for training and tuples of source sentence - image for inference. In this paper, we propose imagiT, a novel machine translation method via visual imagination. ImagiT first learns to generate visual representation from the source sentence, and then utilizes both source sentence and the ``imagined representation'' to produce a target translation. Unlike previous methods, it only needs the source sentence at the inference time. Experiments demonstrate that imagiT benefits from visual imagination and significantly outperforms the text-only neural machine translation baselines. Further analysis reveals that the imagination process in ...
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Keyword:
Artificial Intelligence; Computer Science and Engineering; Intelligent System; Machine Learning; Natural Language Processing
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URL: https://underline.io/lecture/19765-generative-imagination-elevates-machine-translation https://dx.doi.org/10.48448/zv7r-dz88
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Parallel sentences mining with transfer learning in an unsupervised setting ...
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Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation ...
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Detoxifying Language Models Risks Marginalizing Minority Voices ...
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Domain Adaptation for Arabic Cross-Domain and Cross-Dialect Sentiment Analysis from Contextualized Word Embedding ...
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Knowledge Enhanced Masked Language Model for Stance Detection ...
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Frustratingly Easy Edit-based Linguistic Steganography with a Masked Language Model ...
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MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories ...
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DirectProbe: Studying Representations without Classifiers ...
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Challenging distributional models with a conceptual network of philosophical terms ...
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ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding ...
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Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems ...
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CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems ...
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multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning ...
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Modeling Framing in Immigration Discourse on Social Media ...
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Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve ...
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SPLAT: Speech-Language Joint Pre-Training for Spoken Language Understanding ...
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