Language models (LMs) have revolutionized the way we interact with
infor...
Conversational recommender systems (CRS) aim to provide the recommendati...
The research field of Information Retrieval (IR) has evolved significant...
Conversational recommender systems (CRSs) aim to provide recommendation
...
Large-scale pre-trained models (PTMs) have been widely used in
document-...
Auto-regressive search engines emerge as a promising paradigm for next-g...
To better support information retrieval tasks such as web search and
ope...
Recent studies have shown that Dense Retrieval (DR) techniques can
signi...
Learning effective high-order feature interactions is very crucial in th...
Few-shot dense retrieval (DR) aims to effectively generalize to novel se...
Fashion vision-language pre-training models have shown efficacy for a wi...
In this paper, we introduce a new NLP task – generating short factual
ar...
Fine-grained supervision based on object annotations has been widely use...
Label smoothing is a regularization technique widely used in supervised
...
Recent years have witnessed great progress on applying pre-trained langu...
AI creation, such as poem or lyrics generation, has attracted increasing...
Users' search tasks have become increasingly complicated, requiring mult...
Generalized text representations are the foundation of many natural lang...
Previous works show the great potential of pre-trained language models (...
Cross-model retrieval has emerged as one of the most important upgrades ...
The sparsely-activated models have achieved great success in natural lan...
Supersized pre-trained language models have pushed the accuracy of vario...
Pre-trained model such as BERT has been proved to be an effective tool f...
Designing pre-training objectives that more closely resemble the downstr...
As a simple technique to accelerate inference of large-scale pre-trained...