NSFW (Not Safe for Work) content, in the context of a dialogue, can have...
Automatically generating regular expressions (abbrev. regexes) from natu...
Dialogue safety remains a pervasive challenge in open-domain human-machi...
Federated learning (FL) is an emerging distributed machine learning meth...
Researchers have invested considerable effort into ensuring that large
l...
Federated learning has become a popular method to learn from decentraliz...
Despite the recent development in machine learning, most learning system...
Communication success relies heavily on reading participants' reactions....
Data efficiency, or the ability to generalize from a few labeled data,
r...
Vector search has emerged as the foundation for large-scale information
...
Recently, numerous efforts have continued to push up performance boundar...
In deep learning, mixture-of-experts (MoE) activates one or few experts
...
Music representation learning is notoriously difficult for its complex
h...
Current fake audio detection relies on hand-crafted features, which lose...
Existing fake audio detection systems perform well in in-domain testing,...
Semantic Image Synthesis (SIS) is a subclass of image-to-image translati...
There has been an increasing research interest in developing specialized...
This work proposes POMP, a prompt pre-training method for vision-languag...
Although recent approaches aiming for video instance segmentation have
a...
Automatic detection of multimodal fake news has gained a widespread atte...
Due to the significant computational challenge of training large-scale g...
In this paper, we propose Stochastic Knowledge Distillation (SKD) to obt...
Reasoning is a fundamental problem for computers and deeply studied in
A...
Customer churn prediction is a valuable task in many industries. In
tele...
Total knee arthroplasty (TKA) is a common orthopaedic surgery to replace...
Previous soft tissue manipulation studies assumed that the grasping poin...
Federated learning (FL) is an emerging distributed machine learning meth...
This paper analyzes the convergence and generalization of training a
one...
In this demo, we present Chat-to-Design, a new multimodal interaction sy...
The increasingly stringent data privacy regulations limit the developmen...
While there is increasing concern about the interpretability of neural
m...
At online retail platforms, detecting fraudulent accounts and transactio...
Self-supervised learning (SSL) is capable of learning remarkable
represe...
Given labeled data in a source domain, unsupervised domain adaptation ha...
Audio deepfake detection is an emerging topic, which was included in the...
Code-switching is about dealing with alternative languages in the
commun...
Self-training, a semi-supervised learning algorithm, leverages a large a...
Subgraph matching is a NP-complete problem that extracts isomorphic
embe...
The lottery ticket hypothesis (LTH) states that learning on a
properly p...
Person re-identification (ReID) aims to re-identify a person from
non-ov...
Unsupervised representation learning has achieved outstanding performanc...
Named entity recognition (NER) is a widely studied task in natural langu...
Unsupervised domain adaptation has been widely adopted to generalize mod...
Academia and industry have developed several platforms to support the po...
Named entity recognition (NER) is a well-studied task in natural languag...
Transducer-based models, such as RNN-Transducer and transformer-transduc...
The autoregressive (AR) models, such as attention-based encoder-decoder
...
Learning embedding spaces of suitable geometry is critical for represent...
Recent works have demonstrated reasonable success of representation lear...
Attention-based encoder-decoder (AED) models have achieved promising
per...