Mohammad Aliannejadi

Research focuses on enhancing user satisfaction models with balanced datasets.

Research shows multiple queries enhance systems for better information retrieval.

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

Context plays a crucial role in assessing dialogue system performance.

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

Improving document retrieval by optimizing result lists for user experience.

Learn how the TREx framework improves online shopping recommendations.

TREC iKAT aims to improve interactions with conversational agents through personalized dialogues.

A look into how generative IR systems can transform information seeking.

Few-shot indexing improves information retrieval by combining indexing and retrieval processes efficiently.

Researchers discuss the impact of LLMs on evaluating information retrieval systems.

A new approach to assessing how citations support statements in generated text.

Connecting markets to improve product-related question answering.

Explore the evolving world of conversational search through competitions like iKAT.