Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 ha...
The conventional summarization model often fails to capture critical
inf...
Compared to news and chat summarization, the development of meeting
summ...
Communication efficiency and privacy protection are two critical issues ...
Sequential transfer optimization (STO), which aims to improve optimizati...
Distributed stochastic gradient descent (SGD) with gradient compression ...
Data hiding with deep neural networks (DNNs) has experienced impressive
...
The recent popularity of edge devices and Artificial Intelligent of Thin...
Federated recommendation applies federated learning techniques in
recomm...
Embedding-based neural topic models could explicitly represent words and...
Existing dialogue modeling methods have achieved promising performance o...
While conversational semantic role labeling (CSRL) has shown its usefuln...
Contrastive learning has shown great potential in unsupervised sentence
...
Communication bottleneck and data privacy are two critical concerns in
f...
Conversational semantic role labeling (CSRL) is believed to be a crucial...
Gradient-based training in federated learning is known to be vulnerable ...
Gradient quantization is an emerging technique in reducing communication...
Language models like BERT and SpanBERT pretrained on open-domain data ha...
Matrix factorization is an important representation learning algorithm, ...
Semantic role labeling (SRL) aims to extract the arguments for each pred...
The rapid growth in literature accumulates diverse and yet comprehensive...
We study a cooperative multi-agent multi-armed bandits with M agents and...
For multi-turn dialogue rewriting, the capacity of effectively modeling ...
In this paper, we are interested in what we term the federated private
b...
This work is motivated by the need of collecting fresh data from
power-c...
In this paper, we study how to collect fresh data in time-varying networ...
Privacy has raised considerable concerns recently, especially with the a...
We study distributed optimization in the presence of Byzantine adversari...
We provide a process to modify a neural network to an equivariant one, w...
We consider recommendation systems that need to operate under wireless
b...
In the traditional index coding problem, a server employs coding to send...
Caching at the network edge devices such as wireless caching stations (W...
It was recently observed in [1], that in index coding, learning the codi...