Maarten de Rijke

Learn about the efficiency of generative retrieval in document searching.

Learn how feature attribution explains ranking decisions in automated systems.

Research focuses on enhancing user satisfaction models with balanced datasets.

A look into dense and generative retrieval techniques and their impact.

Introducing a framework for more accurate query performance assessment in information retrieval.

A study on the effectiveness of ULTR techniques for search ranking improvements.

Context plays a crucial role in assessing dialogue system performance.

A framework enhances next-point-of-interest recommendations using large language models and contextual data.

User feedback, especially follow-up comments, improves evaluations of dialogue systems.

Improving document retrieval by optimizing result lists for user experience.

A new method to correct for bias in recommendation systems.

Learn how the TREx framework improves online shopping recommendations.

Introducing a method that enhances data summarization across multiple tables based on user queries.

New methods enhance the accuracy of recommendation systems for better user experiences.

A new approach uses LLMs to enhance user recommendations effectively.

A new benchmark assesses how well language models follow multiple instructions in sequence.

BootRet improves document retrieval accuracy with dynamic identifier updates.

This study highlights the importance of dataset granularity in improving image-text retrieval systems.

New approaches enhance ranking systems' safety and effectiveness in online services.

This study investigates the performance of entity linking models in conversational contexts.

A new method improves ranking safety for better user experiences.

Research develops systems that adapt to various question types for better responses.

Ensuring language models provide reliable and accurate information through proper citations.