Junwei Pan

Venues

Frequent coauthors

Papers

1. Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning
   AAAI 2026 ·

   Yipeng Zhang

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2. FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction
   SIGIR 2026 ·

   Zenan Dai

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3. Computational Advertising: Recent Advances
   WWW 2025 · Junwei Pan
4. Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation
   CIKM 2025 ·

   Zhutian Lin

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5. Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs
   CIKM 2025 ·

   Yuhao Wang

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6. From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models
   ICML 2025 ·

   Mingjia Yin

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7. Incremental Learning for LLM-based Tokenization and Recommendation
   CIKM 2025 ·

   Haihan Shi

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8. Long-Sequence Recommendation Models Need Decoupled Embeddings
   ICLR 2025 ·

   Ningya Feng

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9. Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models
   SIGIR 2025 ·

   Yuhao Wang

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10. Towards Unifying Feature Interaction Models for Click-Through Rate Prediction
    ECML-PKDD 2025 ·

    Yu Kang

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11. Ads Recommendation in a Collapsed and Entangled World
    SIGKDD 2024 · Junwei Pan
12. Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning
    AAAI 2024 ·

    Ximei Wang

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13. Deep Pattern Network for Click-Through Rate Prediction
    SIGIR 2024 ·

    Hengyu Zhang

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14. Multi-Sequence Attentive User Representation Learning for Side-information Integrated Sequential Recommendation
    WSDM 2024 ·

    Xiaolin Lin

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15. On the Embedding Collapse when Scaling up Recommendation Models
    ICML 2024 ·

    Xingzhuo Guo

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16. STEM: Unleashing the Power of Embeddings for Multi-Task Recommendation
    AAAI 2024 ·

    Liangcai Su

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17. Temporal Interest Network for User Response Prediction
    WWW 2024 ·

    Haolin Zhou

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18. Understanding the Ranking Loss for Recommendation with Sparse User Feedback
    SIGKDD 2024 ·

    Zhutian Lin

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