Is chatgpt a good recommender? a preliminary study
Recommendation systems have witnessed significant advancements and have been widely
used over the past decades. However, most traditional recommendation methods are task …
used over the past decades. However, most traditional recommendation methods are task …
Prompt learning for news recommendation
Some recent news recommendation (NR) methods introduce a Pre-trained Language Model
(PLM) to encode news representation by following the vanilla pre-train and fine-tune …
(PLM) to encode news representation by following the vanilla pre-train and fine-tune …
[HTML][HTML] A survey of personalized news recommendation
X Meng, H Huo, X Zhang, W Wang, J Zhu - Data Science and Engineering, 2023 - Springer
Personalized news recommendation is an important technology to help users obtain news
information they are interested in and alleviate information overload. In recent years, news …
information they are interested in and alleviate information overload. In recent years, news …
Personalized news recommendation: Methods and challenges
Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …
information and alleviate information overload. Although it has been extensively studied …
Llmrec: Benchmarking large language models on recommendation task
Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has
significantly advanced NLP tasks by enhancing the capabilities of conversational models …
significantly advanced NLP tasks by enhancing the capabilities of conversational models …
Denoising and prompt-tuning for multi-behavior recommendation
In practical recommendation scenarios, users often interact with items under multi-typed
behaviors (eg, click, add-to-cart, and purchase). Traditional collaborative filtering techniques …
behaviors (eg, click, add-to-cart, and purchase). Traditional collaborative filtering techniques …
Mm-rec: Visiolinguistic model empowered multimodal news recommendation
News representation is critical for news recommendation. Most existing methods learn news
representations only from news texts while ignoring the visual information of news. In fact …
representations only from news texts while ignoring the visual information of news. In fact …
On the current state of deep learning for news recommendation
The exponential outbreak of news articles makes it troublesome for the readers to find,
select and read the most relevant ones and alleviate the resulting information and cognitive …
select and read the most relevant ones and alleviate the resulting information and cognitive …
Candidate-aware graph contrastive learning for recommendation
W He, G Sun, J Lu, XS Fang - Proceedings of the 46th International ACM …, 2023 - dl.acm.org
Recently, Graph Neural Networks (GNNs) have become a mainstream recommender system
method, where it captures high-order collaborative signals between nodes by performing …
method, where it captures high-order collaborative signals between nodes by performing …
KEEP: An industrial pre-training framework for online recommendation via knowledge extraction and plugging
An industrial recommender system generally presents a hybrid list that contains results from
multiple subsystems. In practice, each subsystem is optimized with its own feedback data to …
multiple subsystems. In practice, each subsystem is optimized with its own feedback data to …