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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.IR2026

TopoGR: Revealing and Preserving Latent Structure of Semantic ID in Generative Recommendation

Ziyu Zheng, Zhengshun Du, Yaming Yang +5

The paper proposes TopoGR, a generative recommendation framework that uses binary semantic IDs with explicit Hamming geometry to preserve the latent topology of item representation…

cs.AI2026

Can Generative Recommendation Reach Cold Items? A Temporal Perspective on Semantic-ID Generation

Jie Peng, Yanping Zheng, Zhewei Zhe +3

Semantic-ID-based generative recommendation represents items as sequences of shared semantic tokens, enabling token recombination beyond isolated item IDs. However, closed-world re…

cs.LG2026

Cross-Head Attention Uplift Network with Inverse Propensity Score under Unobserved Confounding

Haoran Zhang, Chuanpu Li, Yuxin Fu +4

Uplift modeling, crucial for estimating individual treatment effects (ITE), faces dual challenges: flexibly leveraging inter-group similarity to enhance discriminative power and de…

cs.LG2026

Beyond Leakage and Complexity: Towards Realistic and Efficient Information Cascade Prediction

Jie Peng, Rui Wang, Qiang Wang +4

Information cascade popularity prediction is a key problem in analyzing content diffusion in social networks. However, current related works suffer from three critical limitations:…

cs.SI2026

GRAPHIA: Harnessing Social Graph Data to Enhance LLM-Based Social Simulation

Jiarui Ji, Zehua Zhang, Zhewei Wei +3

Large language models (LLMs) have shown promise in simulating human-like social behaviors. Social graphs provide high-quality supervision signals that encode both local interaction…