I^3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval

Understand

Passage retrieval is a fundamental task in many information systems, such as web search and question answering, where both efficiency and effectiveness are critical concerns.

• In recent years, neural retrievers based on pre-trained language models (PLM), such as dual-encoders, have achieved huge success.
• Yet, studies have found that the performance of dual-encoders are often limited due to the neglecting of the interaction information between queries and candidate passages.
• Therefore, various interaction paradigms have been proposed to improve the performance of vanilla dual-encoders.