Published in ACM TIST, 2026
This paper proposes a gradual domain adaptation framework for graph learning under large distribution shifts.
Recommended citation: Lei Pui Ieng, Chen Ximing, Sheng Yijun, Liu Yanyan, Gong Zhiguo*, & Yang Qiang. (2026). Gradual Domain Adaptation for Graph Learning. ACM Transactions on Intelligent Systems and Technology, 17(5), Article 112, pp. 1–45.
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Published in Knowledge and Information Systems, 2026
This paper models both interest and disinterest collaborative signals for graph-based recommendation.
Recommended citation: Sheng Yijun, Liu Yanyan, Lei Pui Ieng, Chen Ximing, & Gong Zhiguo*. (2026). Dual graph collaborative filtering. Knowledge and Information Systems, 68(1), 182.
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Published in Neurocomputing, 2025
This paper is done by my senior colleague Yanyan.
Recommended citation: Liu Yanyan, Lei Pui Ieng, Sheng Yijun, Chen Ximing, & Gong Zhiguo*. (2025). Efficient energy-based neural topic modeling with embeddings. Neurocomputing, 638, 130179.
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Published in Knowledge-Based Systems, 2025
This paper is my first work.
Recommended citation: Sheng Yijun, Lei Pui Ieng, Liu Yanyan, Chen Ximing, Xu Qiwen, & Gong Zhiguo*. (2025). Dual space multi-granular model for multi-interest sequential recommendation. Knowledge-Based Systems.
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Published in KDD26, 2026
This paper studies diffusion-based recommendation through energy, entropy, and hard-negative sampling.
Recommended citation: Chen Ximing, Lei Pui Ieng, Sheng Yijun, Liu Yanyan, & Gong Zhiguo*. (2026, August). Towards A Tri-View Diffusion Framework for Recommendation. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 116–127.
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Published in WWW26, 2026
This paper improves graph connectivity for collaborative filtering by adaptively reweighting edges.
Recommended citation: Sheng Yijun, Chen Ximing, Lei Pui Ieng, Liu Yanyan, & Gong Zhiguo*. (2026). Adaptive Graph Reweighting for Collaborative Filtering. In Proceedings of the ACM Web Conference (WWW), pp. 5710–5721.
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Published in DASFAA26, 2026
This paper proposes a Forward-Forward framework for graph-based recommendation.
Recommended citation: Chen Ximing, Lei Pui Ieng, Sheng Yijun, Liu Yanyan, & Gong Zhiguo*. (2026, April). Aggregate, Optimize, and Propagate: A Forward-Forward Algorithm Framework for Graph-Based Recommendation. In Database Systems for Advanced Applications (DASFAA), pp. 406–423.
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Published in CIKM25, 2025
This paper is my thid work.
Recommended citation: Sheng Yijun, Chen Ximing, Lei Pui Ieng, Liu Yanyan, & Gong Zhiguo*. (2025, October). Local Structure-Adaptive Graph Filtering for Collaborative Filtering. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), in Press.
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Published in CIKM25, 2025
This paper is my second work.
Recommended citation: Sheng Yijun, Lei Pui Ieng, Liu Yanyan, Chen Ximing, & Gong Zhiguo*. (2025, October). Learning Invariant Reliability under Diverse Contexts for Robust Multimedia Recommendation. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), in Press.
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Published in CIKM24, 2024
This paper is done by my junior colleague Simon.
Recommended citation: Chen Ximing, Lei Pui Ieng, Sheng Yijun, Liu Yanyan, & Gong Zhiguo*. (2024, October). Social influence learning for recommendation systems. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), pp. 312–322.
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