Sichun Luo

Orcid: 0000-0001-8753-9137

According to our database1, Sichun Luo authored at least 15 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Language Model-Based Fine-Grained Address Resolution Framework in UAV Delivery System.
IEEE J. Sel. Top. Signal Process., April, 2024

Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling.
CoRR, 2024

Privacy in LLM-based Recommendation: Recent Advances and Future Directions.
CoRR, 2024

Learning From Correctness Without Prompting Makes LLM Efficient Reasoner.
CoRR, 2024

Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation.
CoRR, 2024

Can LLM Substitute Human Labeling? A Case Study of Fine-grained Chinese Address Entity Recognition Dataset for UAV Delivery.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Large Language Models Augmented Rating Prediction in Recommender System.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation.
CoRR, 2023

PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training.
CoRR, 2023

Improving Long-Tail Item Recommendation with Graph Augmentation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Towards Communication Efficient and Fair Federated Personalized Sequential Recommendation.
CoRR, 2022

HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Personalized Federated Recommendation via Joint Representation Learning, User Clustering, and Model Adaptation.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022


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