Year: 2025
Type: conference-paper
Abstract: In the Web ecosystem, document authors often strategically modify content to maximize visibility in search rankings. These ranking-incentivized modifications pose challenges to retrieval effectiveness, content diversity, and long-term stability. At the same time, the rise of large language models (LLMs) is transforming IR: queries and documents that were once assumed to be generated exclusively by humans can now also be created by automated agents [5]. These agents can formulate queries, generate documents, and perform ranking. This introduces a variety of new challenges and opportunities in competitive search environments, where interactions between strategic agents can substantially influence outcomes.
Author: Haya Nachimovsky
Institution: Technion – Israel Institute of Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funder: Universitas Brawijaya
Award: G6396787490
OpenAlex ID: W4412378084