2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.IR2025
RLRF: Competitive Search Agent Design via Reinforcement Learning from Ranker Feedback
Tommy Mordo, Sagie Dekel, Omer Madmon +2
Competitive search is a setting where document publishers modify them to improve their ranking in response to a query. Recently, publishers have increasingly leveraged LLMs to gene…
cs.IR2025
On the Merits of LLM-Based Corpus Enrichment
Gal Zur, Tommy Mordo, Moshe Tennenholtz +1
Generative AI (genAI) technologies -- specifically, large language models (LLMs) -- and search have evolving relations. We argue for a novel perspective: using genAI to enrich a do…
cs.GT2024★ 2 cited
Sponsored Question Answering
Tommy Mordo, Moshe Tennenholtz, Oren Kurland
The potential move from search to question answering (QA) ignited the question of how should the move from sponsored search to sponsored QA look like. We present the first formal a…