activity
20222026
most citedLinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems

86 citations · 104 across the 8 of their papers we have counts for

collaborators

11 papers

cs.IR2026

Detecting Miscitation on the Scholarly Web through LLM-Augmented Text-Rich Graph Learning

Huidong Wu, Haojia Xiang, Jingtong Gao +3

Scholarly web is a vast network of knowledge connected by citations. However, this system is increasingly compromised by miscitation, where references do not support or even contra…

cs.CL2026

Enhancing Conversational Agents via Task-Oriented Adversarial Memory Adaptation

Yimin Deng, Yuqing Fu, Derong Xu +10

Conversational agents struggle to handle long conversations due to context window limitations. Therefore, memory systems are developed to leverage essential historical information.…

cs.IR2026

PRISM: Purified Representation and Integrated Semantic Modeling for Generative Sequential Recommendation

Dengzhao Fang, Jingtong Gao, Yu Li +2

Generative Sequential Recommendation (GSR) has emerged as a promising paradigm, reframing recommendation as an autoregressive sequence generation task over discrete Semantic IDs (S…

cs.IR20251 cited

HiD-VAE: Interpretable Generative Recommendation via Hierarchical and Disentangled Semantic IDs

Dengzhao Fang, Jingtong Gao, Chengcheng Zhu +3

Recommender systems are indispensable for helping users navigate the immense item catalogs of modern online platforms. Recently, generative recommendation has emerged as a promisin…

cs.LG20251 cited

Graph Federated Learning for Personalized Privacy Recommendation

Ce Na, Kai Yang, Dengzhao Fang +6

Federated recommendation systems (FedRecs) have gained significant attention for providing privacy-preserving recommendation services. However, existing FedRecs assume that all use…

cs.LG2025

Navigate the Unknown: Enhancing LLM Reasoning with Intrinsic Motivation Guided Exploration

Jingtong Gao, Ling Pan, Yejing Wang +6

Reinforcement Learning (RL) has become a key approach for enhancing the reasoning capabilities of large language models. However, prevalent RL approaches like proximal policy optim…