91 citations · 96 across the 13 of their papers we have counts for
16 papers
Learning Robust Personalized Prompts for LLM-Driven Sequential Recommendation
Xiaolin Zheng, Qiyong Zhong, Jiajie Su +1
LLM-driven sequential recommendation formulates next-item prediction as autoregressive generation conditioned on natural-language prompts. However, minor wording changes in semanti…
MAS-OPD: On-Policy Distillation for Multi-agent Systems
Qiyong Zhong, Mao Zheng, Mingyang Song +5
Multi-agent systems (MAS) split a task across specialized roles and are promising on complex tasks, yet a prevailing approach relies on inference-time orchestration alone. General-…
USA: Update-aware SAM for Cross-domain On-Policy Disitllation of Language Agents
Qiyong Zhong, Mao Zheng, Mingyang Song +6
On-policy distillation instils multi-turn agentic reasoning through dense token-level supervision on the student's own trajectories, but a single domain saturates early, so further…
Sharpness-aware Model Merging with Salience Recovery for LLM-based Cross-Domain Sequential Recommendation
Huwei Ji, Jiajie Su, Yuyuan Li +2
LLM-based Cross-Domain Sequential Recommendation (CDSR) leverages LLMs to enhance target performance via deep semantic reasoning, alleviating the dependency on overlapping users. A…
OmniPlan: An Adaptive Framework for Timely and Near-Optimal Network Planning Optimization
Longlong Zhu, Jiashuo Yu, Zedi Chen +12
Network planning optimization is a fundamental problem across diverse domains, including transportation systems, communication networks, and power grids. It requires simultaneous o…
Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment
Haoyuan Wang, Xiaohao Liu, Jiajie Su +2
Multimodal large language models (MLLMs) need efficient mechanisms to update knowledge without degrading existing capabilities. While intrinsic multimodal knowledge editing achieve…
Generalizable Multimodal Large Language Model Editing via Invariant Trajectory Learning
Jiajie Su, Haoyuan Wang, Xiaohua Feng +6
Knowledge editing emerges as a crucial technique for efficiently correcting incorrect or outdated knowledge in large language models (LLM). Existing editing methods rely on a rigid…
Potent but Stealthy: Rethink Profile Pollution against Sequential Recommendation via Bi-level Constrained Reinforcement Paradigm
Jiajie Su, Zihan Nan, Yunshan Ma +6
Sequential Recommenders, which exploit dynamic user intents through interaction sequences, is vulnerable to adversarial attacks. While existing attacks primarily rely on data poiso…
An item is worth one token in Multimodal Large Language Models-based Sequential Recommendation
Qiyong Zhong, Jiajie Su, Ming Yang +3
Sequential recommendations (SR) predict users' future interactions based on their historical behavior. The rise of Large Language Models (LLMs) has brought powerful generative and…
Pctx: Tokenizing Personalized Context for Generative Recommendation
Qiyong Zhong, Jiajie Su, Yunshan Ma +2
Generative recommendation (GR) models tokenize each action into a few discrete tokens (called semantic IDs) and autoregressively generate the next tokens as predictions, showing ad…
Tackling Device Data Distribution Real-time Shift via Prototype-based Parameter Editing
Zheqi Lv, Wenqiao Zhang, Kairui Fu +6
The on-device real-time data distribution shift on devices challenges the generalization of lightweight on-device models. This critical issue is often overlooked in current researc…
Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendation
Jiajie Su, Qiyong Zhong, Yunshan Ma +5
Session-based recommendation (SBR) predicts the next item based on anonymous sessions. Traditional SBR explores user intents based on ID collaborations or auxiliary content. To fur…
Enhancing Attributed Graph Networks with Alignment and Uniformity Constraints for Session-based Recommendation
Xinping Zhao, Chaochao Chen, Jiajie Su +2
Session-based Recommendation (SBR), seeking to predict a user's next action based on an anonymous session, has drawn increasing attention for its practicability. Most SBR models on…
Personalized Behavior-Aware Transformer for Multi-Behavior Sequential Recommendation
Jiajie Su, Chaochao Chen, Zibin Lin +3
Sequential Recommendation (SR) captures users' dynamic preferences by modeling how users transit among items. However, SR models that utilize only single type of behavior interacti…
DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation
Xiaolin Zheng, Jiajie Su, Weiming Liu +1
Sequential Recommendation (SR) characterizes evolving patterns of user behaviors by modeling how users transit among items. However, the short interaction sequences limit the perfo…
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation
Chaochao Chen, Huiwen Wu, Jiajie Su +3
Cross Domain Recommendation (CDR) has been popularly studied to alleviate the cold-start and data sparsity problem commonly existed in recommender systems. CDR models can improve t…