Feng, Fuli

Bias and Debias in Recommender System: A Survey and Future Directions

Chen, J., Dong, H., Wang, X., Feng, F., Wang, M., & He, X. (2023) · ACM Transactions on Information Systems

Recommender Systems and TechniquesEthics and Social Impacts of AI

Cited by 741

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation

Bao, K., Zhang, J., Zhang, Y., Wang, W., Feng, F., & He, X. (2023) · Proceedings of the 17th ACM Conference on Recommender Systems

Recommender Systems and TechniquesTopic Modeling

Cited by 469

Causal Intervention for Leveraging Popularity Bias in Recommendation

Zhang, Y., Feng, F., He, X., Wei, T., Song, C., Ling, G., & Zhang, Y. (2021) · Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 443

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation

Zhang, J., Bao, K., Zhang, Y., Wang, W., Feng, F., & He, X. (2023) · arXiv

Ethics and Social Impacts of AIRecommender Systems and Techniques

Cited by 196

TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

Zhu, F., Lei, W., Huang, Y., Wang, C., Zhang, S., Lv, J., Feng, F., & Chua, T.-S. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Topic ModelingMultimodal Machine Learning Applications

Cited by 193

Data-efficient Fine-tuning for LLM-based Recommendation

Lin, X., Wang, W., Li, Y., Yang, S., Feng, F., Wei, Y., & Chua, T.-S. (2024) · arXiv

Recommender Systems and TechniquesTopic Modeling

Cited by 165

CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation

Zhang, Y., Feng, F., Zhang, J., Bao, K., Wang, Q., & He, X. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 146

Large Language Models are Learnable Planners for Long-Term Recommendation

Shi, W., He, X., Zhang, Y., Gao, C., Li, X., Zhang, J., Wang, Q., & Feng, F. (2024) · Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 35

Generative Recommendation: Towards Next-generation Recommender Paradigm

Wang, W., Lin, X., Feng, F., He, X., & Chua, T.-S. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 34

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models

Bao, K., Zhang, J., Zhang, Y., Huo, X., Chen, C., & Feng, F. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 23

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation

Cai, S., Zhang, J., Bao, K., Gao, C., Wang, Q., Feng, F., & He, X. (2024) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 14

FlowDesign: Improved Design of Antibody CDRs Through Flow Matching and Better Prior Distributions

Wu, J., Kong, X., Sun, N., Wei, J., Shan, S., Feng, F., Wu, F., Peng, J., Zhang, L., Liu, Y., et al. (2024) · Cell Systems

Monoclonal and Polyclonal Antibodies ResearchProtein Structure and Dynamics

Cited by 11

FlowDesign: Improved design of antibody CDRs through flow matching and better prior distributions

Wu, J., Kong, X., Sun, N., Wei, J., Shan, S., Feng, F., Wu, F., Peng, J., Zhang, L., Liu, Y., et al. (2025) · Cell Systems

Monoclonal and Polyclonal Antibodies ResearchProtein Structure and Dynamics

Cited by 11

Decoding in Latent Spaces for Efficient Inference in LLM-based Recommendation

Wang, C., Zhang, Y., Wang, Z., Shi, T., Bao, K., Feng, F., & Chua, T.-S. (2025) · arXiv

Recommender Systems and TechniquesTopic Modeling

Cited by 2

Counterfactual Debating with Preset Stances for Hallucination Elimination of LLMs

Fang, Y., Li, M., Wang, W., Lin, H., & Feng, F. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2