Multimodal stock trading volume movement prediction with stock-related n...
The use of propensity score (PS) methods has become ubiquitous in causal...
In clinical dictation, utterances after automatic speech recognition (AS...
Knowledge graphs (KGs) are commonly used as side information to enhance
...
This paper addresses the prevalent lack of tools to facilitate and empow...
Brain-inspired spiking neuron networks (SNNs) have attracted widespread
...
In-band full-duplex relay (FDR) has attracted much attention as an effec...
Based on binary inquiries, we developed an algorithm to estimate populat...
Dense retrieval is widely used for entity linking to retrieve entities f...
Federated Multilingual Neural Machine Translation (Fed-MNMT) has emerged...
Model substructure learning aims to find an invariant network substructu...
A common countermeasure against side-channel attacks on secret key
crypt...
Co-salient object detection targets at detecting co-existed salient obje...
In recent years, videos and images in 720p (HD), 1080p (FHD) and 4K (UHD...
Recently, end-to-end transformer-based detectors (DETRs) have achieved
r...
The success of transformers in computer vision has led to several attemp...
We introduce a nonconforming virtual element method for the Poisson equa...
Modern systems produce a large volume of logs to record run-time status ...
Open-vocabulary object detection aims to provide object detectors traine...
Recent years have witnessed the unprecedented achievements of large-scal...
While within a clinical study there may be multiple doses and endpoints,...
A reinforcement learning (RL) based method that enables the robot to
acc...
This paper introduces XFL, an industrial-grade federated learning projec...
A well-designed recommender system can accurately capture the attributes...
Preference-based reinforcement learning (PbRL) can enable robots to lear...
When robots learn reward functions using high capacity models that take ...
Network pruning is a promising way to generate light but accurate models...
The foundation models have recently shown excellent performance on a var...
In this report, we present our champion solutions to five tracks at Ego4...
In multi-talker scenarios such as meetings and conversations, speech
pro...
Recently, virtual reality (VR) technology has been widely used in medica...
Recent years have witnessed the dramatic growth of Internet video traffi...
To eliminate the requirement of fully-labeled data for supervised model
...
Arbitrary-oriented object detection is a fundamental task in visual scen...
There has been a recent surge in statistical methods for handling the la...
Video understanding is an important problem in computer vision. Currentl...
Interactive image segmentation aims at segmenting a target region throug...
Gaussian differential privacy (GDP) is a single-parameter family of priv...
In recent years, the rapid development of deep learning has brought grea...
Deep neural networks (DNNs) have been shown to be vulnerable to adversar...
A large amount of document data exists in unstructured form such as raw
...
Controllable text generation systems often leverage control codes to dir...
We consider representation learning on periodic graphs encoding crystal
...
Common causal estimands include the average treatment effect (ATE), the
...
Web applications are becoming more ubiquitous. All manner of physical de...
Amazon Customer Service provides real-time support for millions of custo...
Distributed synchronized GPU training is commonly used for deep learning...
We present DeepGen, a system deployed at web scale for automatically cre...
Spiking neural network (SNN) is a brain-inspired model which has more
sp...
We consider representation learning for proteins with 3D structures. We ...