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Found 15 papers, 4 papers with code
PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation
Pixel synthesis is a promising research paradigm for image generation, which can well exploit pixel-wise prior knowledge for generation.
A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data
The parallel hierarchy enables our model to compare the passage, question, and answer from a variety of trainable perspectives, as opposed to using a manually designed, rigid feature set.
Ranked #1 on
Question Answering
on MCTest-160
Towards Efficient Diffusion-Based Image Editing with Instant Attention Masks
In particular, InstDiffEdit aims to employ the cross-modal attention ability of existing diffusion models to achieve instant mask guidance during the diffusion steps.
Natural Language Generation in Dialogue using Lexicalized and Delexicalized Data
Natural language generation plays a critical role in spoken dialogue systems.
Policy Networks with Two-Stage Training for Dialogue Systems
Indeed, with only a few hundred dialogues collected with a handcrafted policy, the actor-critic deep learner is considerably bootstrapped from a combination of supervised and batch RL.
A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems
The model takes as input a sequence of dialogue contexts and outputs a sequence of dialogue acts corresponding to user intentions.
How to Eliminate Detour Behaviors in E-hailing? Real-time Detecting and Time-dependent Pricing
With the rapid development of information and communication technology (ICT), taxi business becomes a typical electronic commerce mode.
Modelling matrix time series via a tensor CP-decomposition
We consider to model matrix time series based on a tensor CP-decomposition.
Reinforcement learning for multi-item retrieval in the puzzle-based storage system
Nowadays, fast delivery services have created the need for high-density warehouses.
Cautionary Tales on Air-Quality Improvement in Beijing
While this statistic offered some relief for the inhabitants of the capital, we present several analyses based on Beijing's PM2. 5 data of the past 4 years at 36 monitoring sites along with meteorological data of the past 7 years.
Exploiting Expert Knowledge for Assigning Firms to Industries: A Novel Deep Learning Method
To address the limitations of existing methods, we propose a novel deep learning-based method that not only seamlessly integrates the three types of knowledge for industry assignment but also takes the time-specificity of assignment-based knowledge into account.
Deep Learning and Medical Imaging for COVID-19 Diagnosis: A Comprehensive Survey
In this survey, we investigate the main contributions of deep learning applications using medical images in fighting against COVID-19 from the aspects of image classification, lesion localization, and severity quantification, and review different deep learning architectures and some image preprocessing techniques for achieving a preciser diagnosis.
Can LSH (Locality-Sensitive Hashing) Be Replaced by Neural Network?
With the rapid development of GPU (Graphics Processing Unit) technologies and neural networks, we can explore more appropriate data structures and algorithms.
Traffic Video Object Detection using Motion Prior
In this work, we propose two innovative methods to exploit the motion prior and boost the performance of both fully-supervised and semi-supervised traffic video object detection.
