most citedTowards Agentic Recommender Systems in the Era of Multimodal Large Language Models

2 citations · 3 across the 11 of their papers we have counts for

collaborators

14 papers

cs.IR2026

Generative Chain of Behavior for User Trajectory Prediction

Chengkai Huang, Xiaodi Chen, Hongtao Huang +2

Modeling long-term user behavior trajectories is essential for understanding evolving preferences and enabling proactive recommendations. However, most sequential recommenders focu…

cs.CL2026

MemWeaver: Weaving Hybrid Memories for Traceable Long-Horizon Agentic Reasoning

Juexiang Ye, Xue Li, Xinyu Yang +4

Large language model-based agents operating in long-horizon interactions require memory systems that support temporal consistency, multi-hop reasoning, and evidence-grounded reuse…

cs.IR20261 cited

PruneRAG: Confidence-Guided Query Decomposition Trees for Efficient Retrieval-Augmented Generation

Shuguang Jiao, Xinyu Xiao, Yunfan Wei +4

Retrieval-augmented generation (RAG) has become a powerful framework for enhancing large language models in knowledge-intensive and reasoning tasks. However, as reasoning chains de…

cs.CV2026

SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes

Chuhan Wang, Xintong Li, Jennifer Yuntong Zhang +5

Multimodal large language models often struggle with faithful reasoning in complex visual scenes, where intricate entities and relations require precise visual grounding at each st…

cs.IR2025

Listwise Preference Diffusion Optimization for User Behavior Trajectories Prediction

Hongtao Huang, Chengkai Huang, Junda Wu +3

Forecasting multi-step user behavior trajectories requires reasoning over structured preferences across future actions, a challenge overlooked by traditional sequential recommendat…

cs.IR2025

Gaussian Mixture Flow Matching with Domain Alignment for Multi-Domain Sequential Recommendation

Xiaoxin Ye, Chengkai Huang, Hongtao Huang +1

Users increasingly interact with content across multiple domains, resulting in sequential behaviors marked by frequent and complex transitions. While Cross-Domain Sequential Recomm…