Yijun Sheng

Yijun Sheng

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Social influence learning for recommendation systems.

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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Local Structure-Adaptive Graph Filtering for Collaborative Filtering

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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Aggregate, Optimize, and Propagate: A Forward-Forward Algorithm Framework for Graph-Based Recommendation

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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Dual graph collaborative filtering

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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Adaptive Graph Reweighting for Collaborative Filtering

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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Gradual Domain Adaptation for Graph Learning

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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Towards A Tri-View Diffusion Framework for Recommendation

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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