most citedEvaluating the Robustness of Conversational Recommender Systems by Adversarial Examples

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2025

Asking Clarifying Questions for Preference Elicitation With Large Language Models

Ali Montazeralghaem, Guy Tennenholtz, Craig Boutilier +1

Large Language Models (LLMs) have made it possible for recommendation systems to interact with users in open-ended conversational interfaces. In order to personalize LLM responses,…

cs.IR2025

Do LLMs Understand Collaborative Signals? Diagnosis and Repair

Shahrooz Pouryousef, Ali Montazeralghaem

Collaborative information from user-item interactions is a fundamental source of signal in successful recommender systems. Recently, researchers have attempted to incorporate this…

cs.IR2023★ 1 cited

Evaluating the Robustness of Conversational Recommender Systems by Adversarial Examples

Ali Montazeralghaem, James Allan

Conversational recommender systems (CRSs) are improving rapidly, according to the standard recommendation accuracy metrics. However, it is essential to make sure that these systems…