In this work, we introduce the concept of complex text style transfer ta...
Currently, the construction of large language models in specific domains...
With the continuous emergence of Chinese Large Language Models (LLMs), h...
Federated learning (FL) is an important technique for learning models fr...
Controllable text generation has taken a gigantic step forward these day...
Node classification and graph classification are two graph learning prob...
Vertical federated learning (VFL) is a privacy-preserving machine learni...
Variational Auto-Encoder (VAE) has become the de-facto learning paradigm...
Contrastive learning is widely used for recommendation model learning, w...
User modeling is important for news recommendation. Existing methods usu...
News recommendation aims to match news with personalized user interest.
...
News recommendation aims to help online news platform users find their
p...
Ensemble knowledge distillation can extract knowledge from multiple teac...
Single-tower models are widely used in the ranking stage of news
recomme...
Diversity is an important factor in providing high-quality personalized ...
Adversarial learning is a widely used technique in fair representation
l...
Big models are widely used by online recommender systems to boost
recomm...
News recommendation is a core technique used by many online news platfor...
Effectively finetuning pretrained language models (PLMs) is critical for...
Vertical federated learning (VFL) aims to train models from cross-silo d...
Federated learning (FL) is a feasible technique to learn personalized
re...
In this letter, we explored generative image steganography based on
auto...
Text summarization methods have attracted much attention all the time. I...
News recommendation is important for personalized online news services. ...
User modeling is critical for personalized web applications. Existing us...
Federated learning is widely used to learn intelligent models from
decen...
Transformer has achieved great success in NLP. However, the quadratic
co...
Transformer is a powerful model for text understanding. However, it is
i...
News recommendation is often modeled as a sequential recommendation task...
Personalized news recommendation is an important technique to help users...
News recommendation is important for improving news reading experience o...
User interest modeling is critical for personalized news recommendation....
Generative linguistic steganography mainly utilized language models and
...
Personalized news recommendation methods are widely used in online news
...
Transformer is important for text modeling. However, it has difficulty i...
Pre-trained language models (PLMs) achieve great success in NLP. However...
The task of rationalization aims to extract pieces of input text as
rati...
InfoNCE loss is a widely used loss function for contrastive model traini...
The most important task in personalized news recommendation is accurate
...
Personalized news recommendation is an essential technique for online ne...
Accurate news representation is critical for news recommendation. Most o...
Recall and ranking are two critical steps in personalized news
recommend...
Graph neural network (GNN) is widely used for recommendation to model
hi...
Personalized news recommendation techniques are widely adopted by many o...
Pre-trained language models (PLMs) like BERT have made great progress in...
News recommendation is important for online news services. Precise user
...
Transformer has achieved great success in the NLP field by composing var...
Attention mechanism has played critical roles in various state-of-the-ar...
User modeling is critical for many personalized web services. Many exist...
Native ad is a popular type of online advertisement which has similar fo...