Junjie Zhang

Orcid: 0009-0008-8864-915X

Affiliations:
  • Renmin University of China, Beijing, China


According to our database1, Junjie Zhang authored at least 19 papers between 2022 and 2025.

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

Timeline

Legend:

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Links

Online presence:

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Bibliography

2025
Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach.
ACM Trans. Inf. Syst., September, 2025

Review-Enhanced Universal Sequence Representation Learning for Recommender Systems.
ACM Trans. Inf. Syst., May, 2025

SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis.
CoRR, May, 2025

Slow Thinking for Sequential Recommendation.
CoRR, April, 2025

Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis.
ACM Trans. Knowl. Discov. Data, 2025

Frequency-Augmented Mixture-of-Heterogeneous-Experts Framework for Sequential Recommendation.
Proceedings of the ACM on Web Conference 2025, 2025

Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

A Pre-trained Plug-in Mixture-of-LoRAs Model for Transferable Sequential Recommendation.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024
Sequence-level Semantic Representation Fusion for Recommender Systems.
CoRR, 2024

Prompting Large Language Models for Recommender Systems: A Comprehensive Framework and Empirical Analysis.
CoRR, 2024

Distillation is All You Need for Practically Using Different Pre-trained Recommendation Models.
CoRR, 2024

AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems.
Proceedings of the ACM on Web Conference 2024, 2024

AuriSRec: Adversarial User Intention Learning in Sequential Recommendation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Large Language Models are Zero-Shot Rankers for Recommender Systems.
Proceedings of the Advances in Information Retrieval, 2024

Sequence-level Semantic Representation Fusion for Recommender Systems.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
A Survey of Large Language Models.
CoRR, 2023

Towards a More User-Friendly and Easy-to-Use Benchmark Library for Recommender Systems.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Generative Next-Basket Recommendation.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022
Recent Advances in RecBole: Extensions with more Practical Considerations.
CoRR, 2022


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