Using implicit feedback collected from user clicks as training labels for learning-to-rank
algorithms is a well-developed paradigm that has been extensively studied and used in …

Since Information Retrieval (IR) is an interactive process in general, it is important to study
Interactive Information Retrieval (IIR), where we would attempt to model and optimize an …

Pre-trained language model-based neural rankers have been widely applied in information
retrieval (IR). However, the robustness issue of current IR models has not received sufficient …

This paper studies how to enhance the document representation for the bi-encoder
approach in dense document retrieval. The bi-encoder, separately encoding a query and a …

Contextual bandit serves as an invaluable tool to balance the exploration vs. exploitation
tradeoff in various applications such as online recommendation. In many applications …

In the relatively short history of machine learning, the subtle balance between engineering
and theoretical progress has been proved critical at various stages. The most recent wave of …

A common way to extend the memory of large language models (LLMs) is by retrieval
augmented generation (RAG), which inserts text retrieved from a larger memory into an …

Advanced ranking techniques have improved AI-powered information services that
significantly changed people's lives. For example, search engines that rank information …