6 papers
Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation
Qitao Qin, Yucong Luo, Yihang Lu +3
Retrieval-Augmented Generation (RAG), by integrating non-parametric knowledge from external knowledge bases into models, has emerged as a promising approach to enhancing response a…
DARTS: A Dual-View Attack Framework for Targeted Manipulation in Federated Sequential Recommendation
Qitao Qin, Yucong Luo, Zhibo Chu
Federated recommendation (FedRec) preserves user privacy by enabling decentralized training of personalized models, but this architecture is inherently vulnerable to adversarial at…
TimeCapsule: Solving the Jigsaw Puzzle of Long-Term Time Series Forecasting with Compressed Predictive Representations
Yihang Lu, Yangyang Xu, Qitao Qing +1
Recent deep learning models for Long-term Time Series Forecasting (LTSF) often emphasize complex, handcrafted designs, while simpler architectures like linear models or MLPs have o…
Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendation
Yucong Luo, Qitao Qin, Hao Zhang +4
Sequential recommendation (SR) systems have evolved significantly over the past decade, transitioning from traditional collaborative filtering to deep learning approaches and, more…
DV-FSR: A Dual-View Target Attack Framework for Federated Sequential Recommendation
Qitao Qin, Yucong Luo, Mingyue Cheng +2
Federated recommendation (FedRec) preserves user privacy by enabling decentralized training of personalized models, but this architecture is inherently vulnerable to adversarial at…
Leveraging Prior Experience: An Expandable Auxiliary Knowledge Base for Text-to-SQL
Zhibo Chu, Zichong Wang, Qitao Qin
Large Language Models (LLMs) exhibit impressive problem-solving skills across many tasks, but they still underperform compared to humans in various downstream applications, such as…