This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …

The powerful large language models (LLMs) have played a pivotal role in advancing
recommender systems. Recently, in both academia and industry, there has been a surge of …

The debut of ChatGPT has recently attracted significant attention from the natural language
processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT …

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …

The general aim of the recommender system is to provide personalized suggestions to
users, which is opposed to suggesting popular items. However, the normal training …

With the rapid advancements of large language models (LLMs), information retrieval (IR)
systems, such as search engines and recommender systems, have undergone a significant …

Legal case retrieval is a specialized IR task that involves retrieving supporting cases given a
query case. Compared with traditional ad-hoc text retrieval, the legal case retrieval task is …

In general, recommendation can be viewed as a matching problem, ie, match proper items
for proper users. However, due to the huge semantic gap between users and items, it's …

Cross-domain recommendation (CDR) aims to provide better recommendation results in the
target domain with the help of the source domain, which is widely used and explored in real …

Large language models (LLMs) have significantly influenced recommender systems,
spurring interest across academia and industry in leveraging LLMs for recommendation …