Techniques

Which *BERT? A Survey Organizing Contextualized Encoders EMNLP 2020 Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER AAAI 2020 Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity ICLR 2020 Wide Hidden Expansion Layer for Deep Convolutional Neural Networks WACV 2020 With More Contexts Comes Better Performance: Contextualized Sense Embeddings for All-Round Word Sense Disambiguation EMNLP 2020 Word-Level Contextual Sentiment Analysis with Interpretability AAAI 2020 Working Memory-Driven Neural Networks with a Novel Knowledge Enhancement Paradigm for Implicit Discourse Relation Recognition AAAI 2020 X-Linear Attention Networks for Image Captioning CVPR 2020 X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers EMNLP 2020 You Only Train Once: Loss-Conditional Training of Deep Networks ICLR 2020 Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models CVPR 2020 Zero-Shot Neural Machine Translation: Russian-Hindi @LoResMT 2020 AACL 2020 3D Appearance Super-Resolution With Deep Learning CVPR 2019 A2N: Attending to Neighbors for Knowledge Graph Inference ACL 2019 A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes AAAI 2019 ABC: A Big CAD Model Dataset for Geometric Deep Learning CVPR 2019 ABD-Net: Attentive but Diverse Person Re-Identification ICCV 2019 A Benchmark for Interpretability Methods in Deep Neural Networks NeurIPS 2019 A Camera That CNNs: Towards Embedded Neural Networks on Pixel Processor Arrays ICCV 2019 Accelerating Sparse Matrix Operations in Neural Networks on Graphics Processing Units ACL 2019 Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks ICLR 2019 A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis EMNLP 2019 ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks ICCV 2019 A Condition Number for Joint Optimization of Cycle-Consistent Networks NeurIPS 2019 Adaptative Inference Cost With Convolutional Neural Mixture Models ICCV 2019