Research
My research focuses on the intersection of Responsbile AI, including Large Language Models (LLMs) safety, reliability, and privacy.
I also doing my research focuses on Recommender Systems, including Generative Recommendation, Multi-Model Content Understanding, Item Tokenization, Recommendation Scale Law.
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- Excited to be named an Outstanding Campus Recruit for the Algorithm Track at Kuaishou!
- Honored to receive the Outstanding Individual Award in KuaiShou Local Life!
- Excited to share that I've received the Star of Tomorrow Internship Award from MSRA!
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Publications
(* joint first authors)
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2024
Time Matters: Enhancing Pre-trained News Recommendation Models with Robust User Dwell Time Injection
Hao Jiang*, Chuanzhen Li, Mingxiao An
KDD, 2024
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Knowledge Graph Unlearning to Defend Language Model Against Jailbreak Attack
Peihua Mai*, Hao Jiang*, Ran Yan, Youjia Yang, Zhe Huang, Yan Pang
ICLR, Tiny Paper, 2024
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2023
Self-supervised Contrastive Enhancement with Symmetric Few-shot Learning Towers for Cold-start News Recommendation
Hao Jiang, Chuanzhen Li, Juanjuan Cai, Jingling Wang
CIKM, Full Paper, 2023
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RCENR: A Reinforced and Contrastive Heterogeneous Network Reasoning Model for Explainable News Recommendation
Hao Jiang, Chuanzhen Li, Juanjuan Cai, Jingling Wang
SIGIR, Full Paper, 2023
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MNN4Rec: A relation-aware approach based on multi-view news network for news recommendation
Hao Jiang, Chuanzhen Li, Juanjuan Cai, Jingling Wang
Journal of Information Science, 2023
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