In recent years, two time series classification models, ROCKET and
MINIR...
Multi-Domain Recommendation (MDR) has gained significant attention in re...
Click-Through Rate (CTR) prediction is a fundamental technique in
recomm...
Predicting vehicle trajectories is crucial for ensuring automated vehicl...
Model editing techniques modify a minor proportion of knowledge in Large...
Large-scale code generation models such as Codex and CodeT5 have achieve...
Large language models trained on code have shown great potential to incr...
ML-powered code generation aims to assist developers to write code in a ...
We present MBXP, an execution-based code completion benchmark in 10+
pro...
Despite exciting progress in large-scale language generation, the
expres...
Prime factorization is a difficult problem with classical computing, who...
Aggregated stochastic characteristics of geographically distributed wind...
Fermion sampling is to generate probability distribution of a many-body
...
Commuting, like other types of human travel, is complex in nature, such ...
Although deep neural networks generally have fixed network structures, t...
Quantum algorithm design lies in the hallmark of applications of quantum...
With the emerging of touch-less human-computer interaction techniques an...
The contextual information (i.e., the time and location) in which a phot...
In this paper we describe the implementation of a convolutional neural
n...
Binary code analysis allows analyzing binary code without having access ...
Recently, quantum information scrambling has attracted much attention am...
Despite the popularity of deep learning, structure learning for deep mod...
Sparse connectivity is an important factor behind the success of
convolu...
Recently, deep learning based clustering methods are shown superior to
t...