As the size of large language models (LLMs) continues to grow, model
com...
Text-based Visual Question Answering (TextVQA) aims at answering questio...
In the era of large-scale language models, the substantial parameter siz...
This paper introduces a novel targetless method for joint intrinsic and
...
The comprehension of how local interactions arise in global collective
b...
High order fast sweeping methods for efficiently solving steady state
so...
Adaptive network pruning approach has recently drawn significant attenti...
Change captioning is to describe the semantic change between a pair of
s...
We consider a wireless network where N nodes compete for a shared channe...
Contrastive deep graph clustering, which aims to divide nodes into disjo...
The tradeoff between performance and inference speed is critical for
pra...
Accurate localization ability is fundamental in autonomous driving.
Trad...
Most graph-to-text works are built on the encoder-decoder framework with...
For years, the YOLO series has been the de facto industry-level standard...
Federated learning (FL) enables mobile devices to collaboratively learn ...
Weakly supervised Referring Expression Grounding (REG) aims to ground a
...
A non-intrusive model order reduction (MOR) method for solving parameter...
Self-supervised learning (SSL) has achieved promising downstream perform...
Clustering is a representative unsupervised method widely applied in
mul...
Cross-modal hashing is an important approach for multimodal data managem...
Multiple kernel clustering (MKC) is committed to achieving optimal
infor...
Graph neural architecture search has sparked much attention as Graph Neu...
Magnetic soft robots have attracted growing interest due to their unique...
In recent years, creative content generations like style transfer and ne...
Conditional image generation is an active research topic including text2...
Open-vocabulary object detection aims to detect novel object categories
...
Training a generative adversarial network (GAN) with limited data has be...
RGB-infrared person re-identification is an emerging cross-modality
re-i...
Generalizable person re-identification aims to learn a model with only
s...
Recently CKY-based models show great potential in unsupervised grammar
i...
We prove complex contraction for zero-free regions of counting weighted ...
Existing disentangled-based methods for generalizable person
re-identifi...
Change captioning is to use a natural language sentence to describe the
...
In this article, we aim to study the stability and dynamic transition of...
Graph neural networks (GNNs) have been successfully applied to learning
...
We study the problem of localizing audio-visual events that are both aud...
Due to the domain discrepancy in visual domain adaptation, the performan...
Source code can be parsed into the abstract syntax tree (AST) based on
d...
In the electronics industry, introducing Machine Learning (ML)-based
tec...
This paper investigates two typical image-type representations for event...
Graph neural networks (GNNs) emerged recently as a standard toolkit for
...
This paper is concerned with the design of a non-intrusive model order
r...
The continuous convergence of machine learning algorithms, 5G and beyond...
Recent advances in machine learning, wireless communication, and mobile
...
Federated learning (FL) is a new paradigm for large-scale learning tasks...
Table-to-text generation aims at automatically generating natural text t...
Extracting entity pairs along with relation types from unstructured text...
Automated medical image segmentation plays an important role in many cli...
The lateral line enables fish to efficiently sense the surrounding
envir...
Fixed-point iterative sweeping methods were developed in the literature ...