Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction. - Zhangchi Zhu; Lu Wang 029; Pu Zhao 004; Chao Du; Wei Zhang 056; Hang Dong 004; Bo Qiao 001; Qingwei Lin; Saravan Rajmohan; Dongmei Zhang 001 (KDD, 2023)

From Input to Output: A Multi-layer Knowledge Distillation Framework for Compressing Recommendation Models. - Zhangchi Zhu; Wei Zhang (CoRR, 2023)

Contrastive Learning with Negative Sampling Correction. - Lu Wang 029; Chao Du; Pu Zhao 004; Chuan Luo 002; Zhangchi Zhu; Bo Qiao 001; Wei Zhang 056; Qingwei Lin; Saravan Rajmohan; Dongmei Zhang 001; Qi Zhang 066 (CoRR, 2024)

Understanding the Role of Cross-Entropy Loss in Fairly Evaluating Large Language Model-based Recommendation. - Cong Xu; Zhangchi Zhu; Jun Wang 006; Jianyong Wang 001; Wei Zhang 056 (CoRR, 2024)

Are LLM-based Recommenders Already the Best? Simple Scaled Cross-entropy Unleashes the Potential of Traditional Sequential Recommenders. - Cong Xu; Zhangchi Zhu; Mo Yu; Jun Wang 006; Jianyong Wang 001; Wei Zhang 056 (CoRR, 2024)

Exploring Feature-based Knowledge Distillation For Recommender System: A Frequency Perspective. - Zhangchi Zhu; Wei Zhang (CoRR, 2024)

Exploring Feature-based Knowledge Distillation for Recommender System: A Frequency Perspective. - Zhangchi Zhu; Wei Zhang 056 (KDD (1), 2025)

Preference-Consistent Knowledge Distillation for Recommender System. - Zhangchi Zhu; Wei Zhang 056 (IEEE Trans. Knowl. Data Eng., 2025)

Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation. - Minhao Wang; Yunhang He; Cong Xu; Zhangchi Zhu; Wei Zhang 056 (CoRR, 2025)