313 citations · 750 across the 46 of their papers we have counts for
11 papers · 1 filter
Recommendation with Generative Models
Yashar Deldjoo, Zhankui He, Julian McAuley +8
Generative models are a class of AI models capable of creating new instances of data by learning and sampling from their statistical distributions. In recent years, these models ha…
Multi-modal Generative Models in Recommendation System
Arnau Ramisa, Rene Vidal, Yashar Deldjoo +8
Many recommendation systems limit user inputs to text strings or behavior signals such as clicks and purchases, and system outputs to a list of products sorted by relevance. With t…
Large Language Model Driven Recommendation
Anton Korikov, Scott Sanner, Yashar Deldjoo +8
While previous chapters focused on recommendation systems (RSs) based on standardized, non-verbal user feedback such as purchases, views, and clicks -- the advent of LLMs has unloc…
Understanding Modality Preferences in Search Clarification
Leila Tavakoli, Giovanni Castiglia, Federica Calo +3
This study is the first attempt to explore the impact of clarification question modality on user preference in search engines. We introduce the multi-modal search clarification dat…
XAI4LLM. Let Machine Learning Models and LLMs Collaborate for Enhanced In-Context Learning in Healthcare
Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia +1
Clinical decision support systems require models that are not only highly accurate but also equitable and sensitive to the implications of missed diagnoses. In this study, we intro…
A Normative Framework for Benchmarking Consumer Fairness in Large Language Model Recommender System
Yashar Deldjoo, Fatemeh Nazary
The rapid adoption of large language models (LLMs) in recommender systems (RS) presents new challenges in understanding and evaluating their biases, which can result in unfairness…
Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open Challenges
Lemei Zhang, Peng Liu, Yashar Deldjoo +2
The emergence of Large Language Models (LLMs) has achieved tremendous success in the field of Natural Language Processing owing to diverse training paradigms that empower LLMs to e…
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)
Yashar Deldjoo, Zhankui He, Julian McAuley +7
Traditional recommender systems (RS) typically use user-item rating histories as their main data source. However, deep generative models now have the capability to model and sample…
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System
Yashar Deldjoo, Tommaso di Noia
This work takes a critical stance on previous studies concerning fairness evaluation in Large Language Model (LLM)-based recommender systems, which have primarily assessed consumer…
A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender Systems
Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo
In recent years, there has been an increasing recognition that when machine learning (ML) algorithms are used to automate decisions, they may mistreat individuals or groups, with l…
Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and Recency
Yashar Deldjoo
This paper explores the biases in ChatGPT-based recommender systems, focusing on provider fairness (item-side fairness). Through extensive experiments and over a thousand API calls…