Large language models for generative recommendation: A survey and visionary discussions
Recent years have witnessed the wide adoption of large language models (LLM) in different
fields, especially natural language processing and computer vision. Such a trend can also …
fields, especially natural language processing and computer vision. Such a trend can also …
Prompt distillation for efficient llm-based recommendation
Large language models (LLM) have manifested unparalleled modeling capability on various
tasks, eg, multi-step reasoning, but the input to these models is mostly limited to plain text …
tasks, eg, multi-step reasoning, but the input to these models is mostly limited to plain text …
A survey on trustworthy recommender systems
Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …
deployed in almost every corner of the web and facilitate the human decision-making …
Vip5: Towards multimodal foundation models for recommendation
Computer Vision (CV), Natural Language Processing (NLP), and Recommender Systems
(RecSys) are three prominent AI applications that have traditionally developed …
(RecSys) are three prominent AI applications that have traditionally developed …
Up5: Unbiased foundation model for fairness-aware recommendation
Recent advancements in foundation models such as large language models (LLM) have
propelled them to the forefront of recommender systems (RS). Moreover, fairness in RS is …
propelled them to the forefront of recommender systems (RS). Moreover, fairness in RS is …
Understanding biases in chatgpt-based recommender systems: Provider fairness, temporal stability, and recency
Y Deldjoo - ACM Transactions on Recommender Systems, 2024 - dl.acm.org
This paper explores the biases inherent in ChatGPT-based recommender systems, focusing
on provider fairness (item-side fairness). Through extensive experiments and over a …
on provider fairness (item-side fairness). Through extensive experiments and over a …
A Comprehensive Survey on Retrieval Methods in Recommender Systems
In an era dominated by information overload, effective recommender systems are essential
for managing the deluge of data across digital platforms. Multi-stage cascade ranking …
for managing the deluge of data across digital platforms. Multi-stage cascade ranking …
Let me do it for you: Towards llm empowered recommendation via tool learning
Conventional recommender systems (RSs) face challenges in precisely capturing users' fine-
grained preferences. Large language models (LLMs) have shown capabilities in …
grained preferences. Large language models (LLMs) have shown capabilities in …
How can recommender systems benefit from large language models: A survey
With the rapid development of online services, recommender systems (RS) have become
increasingly indispensable for mitigating information overload. Despite remarkable …
increasingly indispensable for mitigating information overload. Despite remarkable …
A preliminary study of chatgpt on news recommendation: Personalization, provider fairness, fake news
Online news platforms commonly employ personalized news recommendation methods to
assist users in discovering interesting articles, and many previous works have utilized …
assist users in discovering interesting articles, and many previous works have utilized …