Enneng Yang

Orcid: 0000-0001-5419-5286

According to our database1, Enneng Yang authored at least 42 papers between 2019 and 2025.

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

Timeline

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Bibliography

2025
Preference Logical Reasoning with Preference Operators for Explainable Recommendations.
ACM Trans. Inf. Syst., July, 2025

Symmetric Graph Contrastive Learning against Noisy Views for Recommendation.
ACM Trans. Inf. Syst., May, 2025

Revisiting Flatness-Aware Optimization in Continual Learning With Orthogonal Gradient Projection.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2025

Unifying Multimodal Large Language Model Capabilities and Modalities via Model Merging.
CoRR, May, 2025

Can LLM-Driven Hard Negative Sampling Empower Collaborative Filtering? Findings and Potentials.
CoRR, April, 2025

Efficient and Adaptive Recommendation Unlearning: A Guided Filtering Framework to Erase Outdated Preferences.
ACM Trans. Inf. Syst., March, 2025

A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2025

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging.
CoRR, January, 2025

Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model.
Proceedings of the ACM on Web Conference 2025, 2025

Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation.
Proceedings of the ACM on Web Conference 2025, 2025

Denoising Multi-Interest-Aware Logical Reasoning for Long-Sequence Recommendation.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Data Augmentation as Free Lunch: Exploring the Test-Time Augmentation for Sequential Recommendation.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Harnessing Content and Structure in ID for Multimodal Recommendation.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Knowledge Decoupling via Orthogonal Projection for Lifelong Editing of Large Language Models.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

EPT: Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

Augmenting Sequential Recommendation with Balanced Relevance and Diversity.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Continual Learning From a Stream of APIs.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Deconfounding User Preference in Recommendation Systems through Implicit and Explicit Feedback.
ACM Trans. Knowl. Discov. Data, September, 2024

Multi-Scenario and Multi-Task Aware Feature Interaction for Recommendation System.
ACM Trans. Knowl. Discov. Data, July, 2024

TiCoSeRec: Augmenting Data to Uniform Sequences by Time Intervals for Effective Recommendation.
IEEE Trans. Knowl. Data Eng., June, 2024

Generalized Embedding Machines for Recommender Systems.
Mach. Intell. Res., June, 2024

PESI: Personalized Explanation recommendation with Sentiment Inconsistency between ratings and reviews.
Knowl. Based Syst., January, 2024

Self-supervised Hierarchical Representation for Medication Recommendation.
CoRR, 2024

Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging.
CoRR, 2024

SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery.
CoRR, 2024

Data Augmentation for Sequential Recommendation: A Survey.
CoRR, 2024

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.
CoRR, 2024

Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion.
CoRR, 2024

Repeated Padding as Data Augmentation for Sequential Recommendation.
CoRR, 2024

Repeated Padding for Sequential Recommendation.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Representation Surgery for Multi-Task Model Merging.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

AdaMerging: Adaptive Model Merging for Multi-Task Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation.
CoRR, 2023

An Efficient Dataset Condensation Plugin and Its Application to Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Data Augmented Flatness-aware Gradient Projection for Continual Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Bi-directional Contrastive Distillation for Multi-behavior Recommendation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2020
Generalized Embedding Machines for Recommender Systems.
CoRR, 2020

2019
Discrete Trust-aware Matrix Factorization for Fast Recommendation.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019


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