Yuyuan Li

Orcid: 0000-0003-4896-2885

Affiliations:

Hangzhou Dianzi University, School of Communication Engineering, Hangzhou, China
Zhejiang University, College of Computer Science, Hangzhou, China

According to our database¹, Yuyuan Li authored at least 55 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

"I See What You Did There": Can Large Vision-Language Models Understand Multimodal Puns?

[BibT_eX]

[DOI]

CoRR, April, 2026

Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems.

[BibT_eX]

[DOI]

CoRR, March, 2026

Sharpness-Aware Minimization for Generalized Embedding Learning in Federated Recommendation.

[BibT_eX]

[DOI]

CoRR, March, 2026

A Survey on Recommendation Unlearning: Fundamentals, Taxonomy, Evaluation, and Open Questions.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., February, 2026

Generalizable Multimodal Large Language Model Editing via Invariant Trajectory Learning.

[BibT_eX]

[DOI]

CoRR, January, 2026

Adaptive eco-cooperative adaptive cruise control for heterogeneous Vehicle platoons using online identification-informed deep reinforcement learning.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2026

Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

Sharpness-Aware Minimization for Generalized Embedding Learning in Federated Recommendation.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

TOFA: Training-Free One-Shot Federated Adaptation for Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Bridging the Copyright Gap: Do Large Vision-Language Models Recognize and Respect Copyrighted Content?

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

DP-GenG: Differentially Private Dataset Distillation Guided by DP-Generated Data.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

FedAU2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

DuAda: Adaptive Targeted Model Poisoning Attack Framework via Dummy User Simulation on Federated Recommendation.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., November, 2025

UFO: Unfair-to-Fair Evolving Mitigates Unfairness in LLM-based Recommender Systems via Self-Play Fine-tuning.

[BibT_eX]

[DOI]

CoRR, November, 2025

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction.

[BibT_eX]

[DOI]

CoRR, July, 2025

BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization.

[BibT_eX]

[DOI]

CoRR, July, 2025

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures.

[BibT_eX]

[DOI]

Muhammad Khurram Khan

Meng Han

CoRR, June, 2025

FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning.

[BibT_eX]

[DOI]

CoRR, June, 2025

RAID: An In-Training Defense against Attribute Inference Attacks in Recommender Systems.

[BibT_eX]

[DOI]

CoRR, April, 2025

Bridging the Gap Between Preference Alignment and Machine Unlearning.

[BibT_eX]

[DOI]

CoRR, April, 2025

A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample-level Unlearning Difficulty.

[BibT_eX]

[DOI]

CoRR, April, 2025

Reproducibility Companion Paper:In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems.

[BibT_eX]

[DOI]

CoRR, March, 2025

Reproducibility Companion Paper: Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems.

[BibT_eX]

[DOI]

CoRR, March, 2025

Post-Training Attribute Unlearning in Recommender Systems.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., January, 2025

Multi-Objective Unlearning in Recommender Systems via Preference Guided Pareto Exploration.

[BibT_eX]

[DOI]

IEEE Trans. Serv. Comput., 2025

Towards Fairness Exploration and Optimization for Digital Service Networks.

[BibT_eX]

[DOI]

IEEE Trans. Serv. Comput., 2025

Class-wise federated unlearning: Harnessing active forgetting with teacher-student memory generation.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2025

Plug and Play: Enabling Pluggable Attribute Unlearning in Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2025, 2025

LEGO: A Lightweight and Efficient Multiple-Attribute Unlearning Framework for Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Multimedia, 2025

Controllable Unlearning for Image-to-Image Generative Models via ϵ-Constrained Optimization.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

MotionStone: Decoupled Motion Intensity Modulation with Diffusion Transformer for Image-to-Video Generation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Making recommender systems forget: Learning and unlearning for erasable recommendation.

[BibT_eX]

[DOI]

Knowl. Based Syst., January, 2024

Integration of large language models and federated learning.

[BibT_eX]

[DOI]

Patterns, 2024

CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models.

[BibT_eX]

[DOI]

CoRR, 2024

WassFFed: Wasserstein Fair Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Controllable Unlearning for Image-to-Image Generative Models via ε-Constrained Optimization.

[BibT_eX]

[DOI]

CoRR, 2024

Post-Training Attribute Unlearning in Recommender Systems.

[BibT_eX]

[DOI]

CoRR, 2024

Hypergraph Convolutional Network for User-Oriented Fairness in Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Check, Locate, Rectify: A Training-Free Layout Calibration System for Text- to- Image Generation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Intra- and Inter-group Optimal Transport for User-Oriented Fairness in Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Selective and collaborative influence function for efficient recommendation unlearning.

[BibT_eX]

[DOI]

Expert Syst. Appl., December, 2023

REFER: Randomized Online Factor Selection Framework for portfolio Management.

[BibT_eX]

[DOI]

Expert Syst. Appl., August, 2023

Federated Unlearning via Active Forgetting.

[BibT_eX]

[DOI]

CoRR, 2023

Selective and Collaborative Influence Function for Efficient Recommendation Unlearning.

[BibT_eX]

[DOI]

CoRR, 2023

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Multimedia, 2023

In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Multimedia, 2023

VoP: Text-Video Co-Operative Prompt Tuning for Cross-Modal Retrieval.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Exponential Gradient with Momentum for Online Portfolio Selection.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2022

Making Recommender Systems Forget: Learning and Unlearning for Erasable Recommendation.

[BibT_eX]

[DOI]

CoRR, 2022

2019

Adaptive Portfolio by Solving Multi-armed Bandit via Thompson Sampling.

[BibT_eX]

[DOI]

CoRR, 2019

Yuyuan Li

Timeline

Legend:

Links

Online presence:

On csauthors.net:

Bibliography

Loading...