Yongsen Zheng

I am currently a Research Fellow in the College of Computing and Data Science at the Nanyang Technological University (NTU), Singapore, and also at the National Centre for Research in Digital Trust, Singapore (Digital Trust Centre Singapore (DTC)) as well as at the Singapore AI Safety Institute (AISI), working with Prof. Kwok-Yan Lam. Prior to that, I obtained my Ph.D. degree in the School of Computer Science and Engineering at Sun Yat-sen University, advised by IEEE Fellow Prof. Liang Lin in HCP-I2 Lab.

I also possess a wealth of experience in the corporate world. Concretely, I have ever interned at Huawei🔥, worked at Tencent🔥, and served as a senior technical consultant at SenseTime🔥.

Human-AI Dialogue System, Conversational Recommender System, Natural Language Processing, Trustworthy AI, AI Safety, Large Language Models, and Causal Reasoning.

Jun, 2025   🔥 One paper is accepted by TKDE 2025.

May, 2025   🔥 Three papers are accepted by ACL 2025.

May, 2025   🔥 One paper "AlphaAgent" is accepted by KDD 2025.

Feb, 2025   🔥 One paper "CRA" is accepted by CVPR 2025. (Highlight)

Feb, 2025   🔥 One paper "Machine Unlearning Survey" is accepted by IEEE OJCS 2025.

Sep, 2024   🔥 One paper "HiCore" is accepted by EMNLP 2024. (Oral)

Jul, 2024   🔥 One paper "CoMoRec" is accepted by ACM MM 2024.

May, 2024   🔥 One paper "HyCoRec" is accepted by ACL 2024. (Oral)

Dec, 2023   🔥 Two papers "FacetCRS" and "Causal Approach" are accepted by AAAI 2024

Oct, 2023   🔥 One paper "HutCRS" is accepted by EMNLP 2023

Jul, 2023   🔥 One paper "Aesthetic Assessment Model" is accepted by ACM MM 2023

Jul, 2023   🔥 One paper "CIPL" is accepted by TNNLS 2023

May, 2023   🔥 One paper "KURIT-Net" is accepted by TNNLS 2023

Jul, 2021   🔥 One paper "GCFM" is accepted by TKDE 2021

Yongsen Zheng, Zongxuan Xie, Guohua Wang, Ziyao Liu, Liang Lin, Kwok-Yan Lam. “Why Multi-Interest Fairness Matters: Hypergraph Contrastive Multi-Interest Learning for Fair Conversational Recommender System”, Association for Computational Linguistic (ACL) 2025 [PDF] [CODE]

Yongsen Zheng, Mingjie Qian, Guohua Wang, Yang Liu, Ziliang Chen, Mingzhi Mao, Liang Lin, Kwok-Yan Lam. “HyperCRS: Hypergraph-Aware Multi-Grained Preference Learning to Burst Filter Bubbles in Conversational Recommendation System”, Association for Computational Linguistic (ACL) 2025 [PDF] [CODE]

Yongsen Zheng, Ruilin Xu, Guohua Wang, Liang Lin, Kwok-Yan Lam. “Mitigating Matthew Effect: Multi-Hypergraph Boosted Multi-Interest Self-Supervised Learning for Conversational Recommendation”, Proc. of Empirical Methods in Natural Language Processing (EMNLP), 2024. [PDF] [CODE]

Yongsen Zheng, Guohua Wang, Yang Liu, Liang Lin. “Diversity Matters: User-Centric Multi-Interest Learning for Conversational Movie Recommendation”, Proc. of ACM International Conference on Multimedia (ACM MM), 2024. [PDF][CODE]

Yongsen Zheng, Ruilin Xu, Ziliang Chen, Guohua Wang, Mingjie Qian, Jinghui Qin, Liang Lin. “HyCoRec: Hypergraph-Enhanced Multi-Preference Learning for Alleviating Matthew Effect in Conversational Recommendation”, Proc. of the Association for Computational Linguistics (ACL), 2024. [PDF] [CODE]

Yongsen Zheng, Ziliang Chen, Jinghui Qin, Liang Lin. “FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2024. [PDF] [CODE]

Yongsen Zheng, Jinghui Qin, Pengxu Wei, Ziliang Chen, Liang Lin. “CIPL: Counterfactual Interactive Policy Learning to Eliminate Popularity Bias for Online Recommendation”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), DOI: 10.1109/TNNLS.2023.3299929, 2023. [PDF] [CODE]

Yongsen Zheng, Pengxu Wei, Ziliang Chen, Chengpei Tang, Liang Lin. “Routing User-Interest Markov Tree for Scalable Personalized Knowledge-Aware Recommendation”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), DOI: 10.1109/TNNLS.2023.3276395, 2023. [PDF] [CODE]

Yongsen Zheng, Pengxu Wei, Ziliang Chen, Yang Cao, Liang Lin. “Graph-Convolved Factorization Machines for Personalized Recommendation”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021. [PDF] [CODE]

Ziyao Liu, Huanyi Ye, Chen Chen, Yongsen Zheng✉, Kwok-Yan Lam. “Threats, Attacks, and Defenses in Machine Unlearning: A Survey”, IEEE Open Journal of the Computer Society (IEEE OJCS), 2025. [PDF] [CODE]

Guohua Wang, Shengping Song, Wuchun He, Yongsen Zheng✉, “CMHKF: Cross-Modality Heterogeneous Knowledge Fusion for Weakly Supervised Video Anomaly Detection”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), 2025. [PDF] [CODE]

Xin Jin, Wu Zhou, Jinyu Wang, Duo Xu, Yongsen Zheng✉. “An Order-Complexity Aesthetic Assessment Model for Aesthetic-aware Music Recommendation”, Proc. of ACM International Conference on Multimedia (ACM MM), 2023. [PDF] [CODE]

Mingjie Qian*, Yongsen Zheng*, Jinghui Qin, Liang Lin. “HutCRS: Hierarchical User-Interest Tracking for Conversational Recommender System”, Proc. of Empirical Methods in Natural Language Processing (EMNLP), 2023. [PDF] [CODE]

Yang Liu, Binglin Chen, Yongsen Zheng, Lechao Cheng, Guanbin Li, Liang Lin. “ODMixer: Fine-grained Spatial-temporal MLP for Metro Origin-Destination Prediction”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2025. [PDF] [CODE]

Ziyi Tang, Zechuan Chen, Jiarui Yang, Jiayao Mai, Yongsen Zheng, Keze Wang, Jinrui Chen, Liang Lin. “AlphaAgent: LLM-Driven Alpha Mining with Regularized Exploration to Counteract Alpha Decay”, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025. [PDF] [CODE]

Weixing Chen, Yang Liu, Binglin Chen, Jiandong Su, Yongsen Zheng, Liang Lin. “Cross-modal Causal Relation Alignment for Video Question Grounding”, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025. [PDF] [CODE]

Ziliang Chen, Yongsen Zheng, Zhao-Rong Lai, Quanlong Guan, Liang Lin. “Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach”, Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2024. [PDF] [CODE]