471 citations · 844 across the 14 of their papers we have counts for
14 papers
Shape Your Feed: An LLM-based Agentic System for Conversational Recommendation
Ziyun Xu, Bosen Ding, Yue Zhang +10
Industrial recommendation systems predominantly adopt a passive ranking paradigm that infers user preferences from implicit behavioral signals (e.g., clicks, dwell time) rather tha…
Bumblebee: Interleaved Mixed-Layer Building Blocks for Large-Scale Recommendation Systems
David Bauer, Cancan Zhang, Wenshun Liu +13
Recommendation systems have undergone significant transformations in the past years. The transition from traditional feature interaction modules to generative next-action predictio…
A General Framework for Multimodal LLM-Based Multimedia Understanding in Large-Scale Recommendation Systems
Yiming Zhu, Xu Liu, Ziyun Xu +9
Conventional recommendation systems frequently fail to fully exploit the high-dimensional semantic signals inherent in multimedia content, thereby limiting the fidelity of user pre…
Objective Shaping with Hard Negatives: Windowed Partial AUC Optimization for RL-based LLM Recommenders
Wentao Shi, Qifan Wang, Chen Chen +7
Reinforcement learning (RL) effectively optimizes Large Language Model (LLM)-based recommenders by contrasting positive and negative items. Empirically, training with beam-search n…
Deep Reinforcement Learning for Personalized Search Story Recommendation
Jason, Zhang, Junming Yin +2
In recent years, \emph{search story}, a combined display with other organic channels, has become a major source of user traffic on platforms such as e-commerce search platforms, ne…
Demystifying Core Ranking in Pinterest Image Search
Linhong Zhu
Pinterest Image Search Engine helps hundreds of millions of users discover interesting content everyday. This motivates us to improve the image search quality by evolving our ranki…
Label Propagation on K-partite Graphs with Heterophily
Dingxiong Deng, Fan Bai, Yiqi Tang +3
In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption. Homophily label propagation (i.e., two connected nodes share sim…
Temporal Learning and Sequence Modeling for a Job Recommender System
Kuan Liu, Xing Shi, Anoop Kumar +2
We present our solution to the job recommendation task for RecSys Challenge 2016. The main contribution of our work is to combine temporal learning with sequence modeling to captur…
Latent Space Model for Road Networks to Predict Time-Varying Traffic
Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek +3
Real-time traffic prediction from high-fidelity spatiotemporal traffic sensor datasets is an important problem for intelligent transportation systems and sustainability. However, i…
Attention Inequality in Social Media
Linhong Zhu, Kristina Lerman
Social media can be viewed as a social system where the currency is attention. People post content and interact with others to attract attention and gain new followers. In this pap…
The DARPA Twitter Bot Challenge
V. S. Subrahmanian, Amos Azaria, Skylar Durst +18
A number of organizations ranging from terrorist groups such as ISIS to politicians and nation states reportedly conduct explicit campaigns to influence opinion on social media, po…
Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization
Linhong Zhu, Dong Guo, Junming Yin +2
We propose a scalable temporal latent space model for link prediction in dynamic social networks, where the goal is to predict links over time based on a sequence of previous graph…
Partitioning Networks with Node Attributes by Compressing Information Flow
Laura M. Smith, Linhong Zhu, Kristina Lerman +1
Real-world networks are often organized as modules or communities of similar nodes that serve as functional units. These networks are also rich in content, with nodes having distin…
Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media
Linhong Zhu, Aram Galstyan, James Cheng +1
The growing popularity of social media (e.g, Twitter) allows users to easily share information with each other and influence others by expressing their own sentiments on various su…