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Found 7 papers, 3 papers with code
Language Tokens: Simply Improving Zero-Shot Multi-Aligned Translation in Encoder-Decoder Models
In a WMT-based setting, we see 1. 3 and 0. 4 BLEU points improvement for the zero-shot setting, and when using direct data for training, respectively, while from-English performance improves by 4. 17 and 0. 85 BLEU points.
Simply Trainable Nearest Neighbour Machine Translation with GPU Inference
Experimental results on different domains show that our proposed method either improves or sometimes maintain the translation quality of methods in Dai et al. while being automatic.
Language Tokens: A Frustratingly Simple Approach Improves Zero-Shot Performance of Multilingual Translation
In a WMT evaluation campaign, From-English performance improves by 4. 17 and 2. 87 BLEU points, in the zero-shot setting, and when direct data is available for training, respectively.
AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks
With the booming demand for machine learning applications, it has been recognized that the number of knowledgeable data scientists can not scale with the growing data volumes and application needs in our digital world.
Instance-based Label Smoothing For Better Calibrated Classification Networks
Label smoothing is widely used in deep neural networks for multi-class classification.
Comprehensive Empirical Evaluation of Deep Learning Approaches for Session-based Recommendation in E-Commerce
In this work, we present a comprehensive evaluation of the state-of-the-art deep learning approaches used in the session-based recommendation.
Automated Machine Learning: State-of-The-Art and Open Challenges
Furthermore, we provide comprehensive coverage for the various tools and frameworks that have been introduced in this domain.
