Attention has arguably become one of the most important concepts in the deep learning
field. It is inspired by the biological systems of humans that tend to focus on the distinctive …

Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

Ranking models lie at the heart of research on information retrieval (IR). During the past
decades, different techniques have been proposed for constructing ranking models, from …

Artificial intelligence (AI) has significantly impacted various fields. Large language models
(LLMs) like GPT-4, BARD, PaLM, Megatron-Turing NLG, Jurassic-1 Jumbo etc., have …

Natural language sentence matching is a fundamental technology for a variety of tasks.
Previous approaches either match sentences from a single direction or only apply single …

With the increasing computational demands of the neural networks, many hardware
accelerators for the neural networks have been proposed. Such existing neural network …

With the rapid growth of knowledge bases (KBs) on the web, how to take full advantage of
them becomes increasingly important. Question answering over knowledge base (KB-QA) is …

Since Google proposed Transformer in 2017, it has made significant natural language
processing (NLP) development. However, the increasing cost is a large amount of …