Recently, Large Language Models (LLMs) have achieved amazing zero-shot
l...
Text-to-image synthesis for the Chinese language poses unique challenges...
Text classification is one of the most imperative tasks in natural langu...
In recent years, diffusion models have emerged as the most powerful appr...
Diffusion models and large language models have emerged as leading-edge
...
This paper presents a new vision Transformer, Scale-Aware Modulation
Tra...
Split learning enables collaborative deep learning model training while
...
Large-scale pre-trained text-image models with dual-encoder architecture...
Fine-tuning large pre-trained language models on various downstream task...
In recent years, diffusion models have become the most popular and power...
Neural sequence labeling (NSL) aims at assigning labels for input langua...
In this paper, we study the non-monotone DR-submodular function maximiza...
Federated Learning (FL) is pervasive in privacy-focused IoT environments...
Few-shot Named Entity Recognition (NER) aims to identify named entities ...
Recently, knowledge-enhanced pre-trained language models (KEPLMs) improv...
We develop an all-in-one computer vision toolbox named EasyCV to facilit...
Extractive Question Answering (EQA) is one of the most important tasks i...
The success of Pre-Trained Models (PTMs) has reshaped the development of...
Pre-trained Language Models (PLMs) have achieved remarkable performance ...
Pre-trained Language Models (PLMs) have achieved great success in variou...
Knowledge-Enhanced Pre-trained Language Models (KEPLMs) are pre-trained
...
In speech enhancement, complex neural network has shown promising perfor...
Low-power wide-area network technologies such as LoRaWAN are promising f...
Multi-label image classification (MLIC) is a fundamental and practical t...
Recent trend towards increasing large machine learning models require bo...
Pre-trained language models have been applied to various NLP tasks with
...
Intelligent personal assistant systems for information-seeking conversat...
The literature has witnessed the success of applying deep Transfer Learn...
The intensive computation of Automatic Speech Recognition (ASR) models
o...
We present EasyASR, a distributed machine learning platform for training...
Structured information extraction from document images usually consists ...
Machine Reading Comprehension (MRC) aims to extract answers to questions...
Building Automatic Speech Recognition (ASR) systems from scratch is
sign...
Spatial attention has been introduced to convolutional neural networks (...
Multi-label learning deals with the problem that each instance is associ...
Pre-trained neural language models bring significant improvement for var...
Swapping text in scene images while preserving original fonts, colors, s...
Lexical relations describe how concepts are semantically related, in the...
Large pre-trained language models such as BERT have shown their effectiv...
Mobility is the backbone of urban life and a vital economic factor in th...
Low-power wide-area network technologies such as LoRaWAN are important f...
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge,
p...
Deep text matching approaches have been widely studied for many applicat...
Product reviews, in the form of texts dominantly, significantly help
con...
Building multi-turn information-seeking conversation systems is an impor...
Intelligent personal assistant systems with either text-based or voice-b...
We present AliMe Assist, an intelligent assistant designed for creating ...
In this paper, we study transfer learning for the PI and NLI problems, a...
We present PS-DBSCAN, a communication efficient parallel DBSCAN algorith...