How Can Recommender Systems Benefit from Large Language Models: A Survey J Lin, X Dai, Y Xi, W Liu, B Chen, H Zhang, Y Liu, C Wu, X Li, C Zhu, ... arXiv preprint arXiv:2306.05817, 2023 | 79* | 2023 |
Towards open-world recommendation with knowledge augmentation from large language models Y Xi, W Liu, J Lin, J Zhu, B Chen, R Tang, W Zhang, R Zhang, Y Yu arXiv preprint arXiv:2306.10933, 2023 | 49 | 2023 |
A graph-enhanced click model for web search J Lin, W Liu, X Dai, W Zhang, S Li, R Tang, X He, J Hao, Y Yu Proceedings of the 44th international ACM SIGIR conference on research and …, 2021 | 32 | 2021 |
An adversarial imitation click model for information retrieval X Dai, J Lin, W Zhang, S Li, W Liu, R Tang, X He, J Hao, J Wang, Y Yu Proceedings of the Web Conference 2021, 1809-1820, 2021 | 29 | 2021 |
Rella: Retrieval-enhanced large language models for lifelong sequential behavior comprehension in recommendation J Lin, R Shan, C Zhu, K Du, B Chen, S Quan, R Tang, Y Yu, W Zhang arXiv preprint arXiv:2308.11131, 2023 | 25* | 2023 |
A Bird's-eye View of Reranking: from List Level to Page Level Y Xi*, J Lin*, W Liu, X Dai, W Zhang, R Zhang, R Tang, Y Yu Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 15 | 2023 |
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction J Lin, Y Qu, W Guo, X Dai, R Tang, Y Yu, W Zhang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 11 | 2023 |
Learning ball-balancing robot through deep reinforcement learning Y Zhou, J Lin, S Wang, C Zhang 2021 International Conference on Computer, Control and Robotics (ICCCR), 1-8, 2021 | 11 | 2021 |
An f-shape click model for information retrieval on multi-block mobile pages L Fu*, J Lin*, W Liu, R Tang, W Zhang, R Zhang, Y Yu Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 10 | 2023 |
Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models C Liu, J Lin, J Wang, H Liu, J Caverlee arXiv preprint arXiv:2403.03900, 2024 | 3 | 2024 |
FLIP: Towards Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction H Wang*, J Lin*, X Li, B Chen, C Zhu, R Tang, W Zhang, Y Yu arXiv preprint arXiv:2310.19453, 2023 | 2* | 2023 |
Codeapex: A bilingual programming evaluation benchmark for large language models L Fu, H Chai, S Luo, K Du, W Zhang, L Fan, J Lei, R Rui, J Lin, Y Fang, ... arXiv preprint arXiv:2309.01940, 2023 | 2 | 2023 |
Towards Efficient and Effective Unlearning of Large Language Models for Recommendation H Wang*, J Lin*, B Chen, Y Yang, R Tang, W Zhang, Y Yu arXiv preprint arXiv:2403.03536, 2024 | 1 | 2024 |
Retrieval-Oriented Knowledge for Click-Through Rate Prediction H Liu, B Chen, M Zhu, J Lin, J Qin, Y Yang, H Zhang, R Tang arXiv preprint arXiv:2404.18304, 2024 | | 2024 |
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation J Zhu, Y Wang, J Lin, J Qin, R Tang, W Zhang, Y Yu arXiv preprint arXiv:2404.07581, 2024 | | 2024 |
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models Y Xi, W Liu, J Lin, C Wu, B Chen, R Tang, W Zhang, Y Yu arXiv preprint arXiv:2403.16378, 2024 | | 2024 |
Adversarially Trained Environment Models Are Effective Policy Evaluators and Improvers-An Application to Information Retrieval Y Li, Y Liu, X Dai, J Lin, H Lai, Y Liu, Y Yu Proceedings of the Fifth International Conference on Distributed Artificial …, 2023 | | 2023 |
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction J Lin, B Chen, H Wang, Y Xi, Y Qu, X Dai, K Zhang, R Tang, Y Yu, ... arXiv preprint arXiv:2310.09234, 2023 | | 2023 |