activity
20232026
most citedAPGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation

25 citations · 34 across the 25 of their papers we have counts for

collaborators
Showing 2025Show all

7 papers · 1 filter

cs.IR2025

FuXi-β: Towards a Lightweight and Fast Large-Scale Generative Recommendation Model

Yufei Ye, Wei Guo, Hao Wang +7

Scaling laws for autoregressive generative recommenders reveal potential for larger, more versatile systems but mean greater latency and training costs. To accelerate training and…

cs.CL2025

Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent

Haocheng Yu, Yaxiong Wu, Hao Wang +6

Interactive recommendation is a typical information-seeking task that allows users to interactively express their needs through natural language and obtain personalized recommendat…

cs.IR2025

Killing Two Birds with One Stone: Unifying Retrieval and Ranking with a Single Generative Recommendation Model

Luankang Zhang, Kenan Song, Yi Quan Lee +7

In recommendation systems, the traditional multi-stage paradigm, which includes retrieval and ranking, often suffers from information loss between stages and diminishes performance…

cs.IR2025

Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation

Qijiong Liu, Jieming Zhu, Lu Fan +5

In recent years, integrating large language models (LLMs) into recommender systems has created new opportunities for improving recommendation quality. However, a comprehensive benc…

cs.IR2025

A Universal Framework for Compressing Embeddings in CTR Prediction

Kefan Wang, Hao Wang, Kenan Song +6

Accurate click-through rate (CTR) prediction is vital for online advertising and recommendation systems. Recent deep learning advancements have improved the ability to capture feat…

cs.IR2025

Generative Large Recommendation Models: Emerging Trends in LLMs for Recommendation

Hao Wang, Wei Guo, Luankang Zhang +7

In the era of information overload, recommendation systems play a pivotal role in filtering data and delivering personalized content. Recent advancements in feature interaction and…

cs.IR2025

FuXi-: Scaling Recommendation Model with Feature Interaction Enhanced Transformer

Yufei Ye, Wei Guo, Jin Yao Chin +8

Inspired by scaling laws and large language models, research on large-scale recommendation models has gained significant attention. Recent advancements have shown that expanding se…