Horizontal federated recommender system: A survey
Due to underlying privacy-sensitive information in user-item interaction data, the risk of
privacy leakage exists in the centralized-training recommender system (RecSys). To this …
privacy leakage exists in the centralized-training recommender system (RecSys). To this …
Embedding compression in recommender systems: A survey
To alleviate the problem of information explosion, recommender systems are widely
deployed to provide personalized information filtering services. Usually, embedding tables …
deployed to provide personalized information filtering services. Usually, embedding tables …
Where to go next for recommender systems? id-vs. modality-based recommender models revisited
Recommendation models that utilize unique identities (IDs for short) to represent distinct
users and items have been state-of-the-art (SOTA) and dominated the recommender …
users and items have been state-of-the-art (SOTA) and dominated the recommender …
Recbole 2.0: Towards a more up-to-date recommendation library
In order to support the study of recent advances in recommender systems, this paper
presents an extended recommendation library consisting of eight packages for up-to-date …
presents an extended recommendation library consisting of eight packages for up-to-date …
FinalMLP: an enhanced two-stream MLP model for CTR prediction
Click-through rate (CTR) prediction is one of the fundamental tasks in online advertising and
recommendation. Multi-layer perceptron (MLP) serves as a core component in many deep …
recommendation. Multi-layer perceptron (MLP) serves as a core component in many deep …
Humanmac: Masked motion completion for human motion prediction
Human motion prediction is a classical problem in computer vision and computer graphics,
which has a wide range of practical applications. Previous effects achieve great empirical …
which has a wide range of practical applications. Previous effects achieve great empirical …
Multimodal pretraining, adaptation, and generation for recommendation: A survey
Personalized recommendation serves as a ubiquitous channel for users to discover
information tailored to their interests. However, traditional recommendation models primarily …
information tailored to their interests. However, traditional recommendation models primarily …
Localvaluebench: A collaboratively built and extensible benchmark for evaluating localized value alignment and ethical safety in large language models
GI Meadows, NWL Lau, EA Susanto, CL Yu… - arxiv preprint arxiv …, 2024 - arxiv.org
The proliferation of large language models (LLMs) requires robust evaluation of their
alignment with local values and ethical standards, especially as existing benchmarks often …
alignment with local values and ethical standards, especially as existing benchmarks often …
Towards deeper, lighter and interpretable cross network for CTR prediction
Click Through Rate (CTR) prediction plays an essential role in recommender systems and
online advertising. It is crucial to effectively model feature interactions to improve the …
online advertising. It is crucial to effectively model feature interactions to improve the …
From clicks to carbon: The environmental toll of recommender systems
As global warming soars, the need to assess the environmental impact of research is
becoming increasingly urgent. Despite this, few recommender systems research papers …
becoming increasingly urgent. Despite this, few recommender systems research papers …