35 citations · 41 across the 22 of their papers we have counts for
9 papers · 1 filter
MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI Recommendation
Ziqing Wu, Zhu Sun, Dongxia Wang +3
Large language models (LLMs) have shown promising potential for next Point-of-Interest (POI) recommendation. However, existing methods only perform direct zero-shot prompting, lead…
The Digital Ecosystem of Beliefs: does evolution favour AI over humans?
David M. Bossens, Shanshan Feng, Yew-Soon Ong
As AI systems are integrated into social networks, there are AI safety concerns that AI-generated content may dominate the web, e.g. in popularity or impact on beliefs. To understa…
Prototype Optimization with Neural ODE for Few-Shot Learning
Baoquan Zhang, Shanshan Feng, Bingqi Shan +3
Few-Shot Learning (FSL) is a challenging task, which aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a…
Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons
Jiao Liu, Zhu Sun, Shanshan Feng +2
In the evolutionary computing community, the remarkable language-handling capabilities and reasoning power of large language models (LLMs) have significantly enhanced the functiona…
Hybrid Memetic Search for Electric Vehicle Routing with Time Windows, Simultaneous Pickup-Delivery, and Partial Recharges
Zubin Zheng, Shengcai Liu, Yew-Soon Ong
With growing environmental concerns, electric vehicles for logistics have gained significant attention within the computational intelligence community in recent years. This work ad…
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning
Mengmeng Chen, Xiaohu Wu, Xiaoli Tang +5
Federated learning (FL) is a machine learning paradigm that allows multiple FL participants (FL-PTs) to collaborate on training models without sharing private data. Due to data het…
Learning Structurally Stabilized Representations for Multi-modal Lossless DNA Storage
Ben Cao, Tiantian He, Xue Li +4
In this paper, we present Reed-Solomon coded single-stranded representation learning (RSRL), a novel end-to-end model for learning representations for multi-modal lossless DNA stor…
Road Network Representation Learning with the Third Law of Geography
Haicang Zhou, Weiming Huang, Yile Chen +3
Road network representation learning aims to learn compressed and effective vectorized representations for road segments that are applicable to numerous tasks. In this paper, we id…
LIST: Learning to Index Spatio-Textual Data for Embedding based Spatial Keyword Queries
Ziqi Yin, Shanshan Feng, Shang Liu +3
With the proliferation of spatio-textual data, Top-k KNN spatial keyword queries (TkQs), which return a list of objects based on a ranking function that considers both spatial and…