arXiv:2602. 12972v2 Announce Type: replace-cross Abstract: In online advertising, marketing interventions such as coupons introduce significant confounding bias into Click-Through Rate (CTR) prediction.
By Siyun Yang, Shixiao Yang, Jian Wang, Di Fan, Kehe Cai, Haoyan Fu, Jiaming Zhang, Wenjin Wu, Peng Jiang
arXiv:2607. 05242v1 Announce Type: cross Abstract: Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE).
By Zuwang He, Shihao Shu, Yuli Qu, Hanyu Gao, Ziliang Zhang, Diwei Chen, Xiangda Yan, Buyu Gao, Tanchao Zhu, Yumeng Li, Junxiong Zhu
PaGNet is a hybrid panel‑aware model that combines a LightGBM branch with panel‑temporal summaries and a Panel‑MLP branch using attention‑pooled aggregation and shared‑trunk multi‑task learning. It produces predictions for corporate tax avoidance proxies while providing a per‑target diagnostic that indicates which branch contributed most to each forecast. On a panel of 1,754 Korean firms, PaGNet improves explained variance over six baselines by 0.08–0.11 on key accrual targets and demonstrates stable routing and diagnostic consistency across different feature regimes.
By Wonho Song, Hyungjoon Kim
arXiv:2607. 08202v1 Announce Type: new Abstract: Estimating original-space conditional expectations is central to value-driven recommender systems, including dwell time, GMV, and LTV forecasting.
By Mingyu Zhao, Zhaohan Li, Zhenxiong Miao, Xu Zhang, Dewei Leng, Yanan Niu, Kun Gai
Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). However, traditional models often fail in complex multi-seller environments with violations of the Stable Unit Treatment Value Assumption (SUTVA).
arXiv:2609.24559v1 Announce Type: new
Abstract: We present $t_0$, a family of open-weights foundation models for forecasting with multivariate context. We release its first two members: $\texttt{t0-a...
By Lucas Meyer, Claudio Sole, Huikan Xiang, Nicolas Li, Lucas Franceschino, Arnau Quera-Bofarull, Maarten P. Scholl, Joachim Fainberg, Geoffrey N\'egiar