SIGIR

Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems

自适应自引导的扩散推荐系统中物品层面公平性

Zihan Li, Gustavo Escobedo, Marta Moscati, Oleg Lesota, Markus Schedl

AI总结 本文提出A2G-DiffRec，通过自适应自引导提升扩散推荐系统中物品层面的公平性，在牺牲少量准确率的情况下有效平衡不同流行度物品的曝光。

Comments Accepted at SIGIR 2026

Rethinking Semantic Collaborative Integration: Why Alignment Is Not Enough

重新思考语义协作整合：为什么对齐不够

Maolin Wang, Dongze Wu, Jianing Zhou, Hongyu Chen, Beining Bao, Yu Jiang, Chenbin Zhang, Chang Wang, Jian Liu, Lei Sha

AI总结 本文挑战了传统语义与协作表示对齐的假设，提出互补融合视角，强调共享与私有因素的区分，通过实验揭示语义与协作视图的低一致性及互补性，倡导以互补性为核心的推荐系统设计。

Comments Accepted by SIGIR 2026

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

KuaiLive: 一个实时互动数据集用于直播推荐

Changle Qu, Sunhao Dai, Ke Guo, Xiao Zhang, Liqin Zhao, Shijun Wang, Yannan Niu, Lantao Hu, Han Li, Jun Xu

机构 * Gaoling School of Artificial Intelligence\ University of China Beijing China ； Gaoling School of Artificial Intelligence\ University of China 纠错

AI总结 KuaiLive是一个实时互动数据集，用于直播推荐研究，包含精确的时间戳、多种实时用户交互和丰富的用户及主播侧信息，支持多种推荐任务和多行为建模。

Comments Accepted by SIGIR 2026