arXiv:2606. 26690v1 Announce Type: cross Abstract: In large-scale paid acquisition and growth advertising systems, production attribution outputs are widely used for daily budget allocation and channel diagnosis.
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: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).
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.
arXiv:2603. 20775v2 Announce Type: replace Abstract: In personalized marketing, uplift models estimate the incremental effect of an intervention by modeling how customer behavior would change under alternative treatments using counterfactual analysis.
arXiv:2608. 10562v1 Announce Type: new Abstract: Not all clicks are equal.
arXiv:2607. 14418v1 Announce Type: new Abstract: Ad-load design is a central supply-side decision in sponsored search: more sponsored slots can raise revenue, but may crowd out organic results and degrade user outcomes.
arXiv:2606. 16878v1 Announce Type: new Abstract: Retail marketing measurement increasingly requires granular campaign-level insights without relying on user-level tracking.
The paper introduces an adequacy‑aware calibration protocol for generative social simulators that integrates amortized posterior estimation, synthetic identifiability assessment, matched‑sample‑size adequacy checks, diagnosis‑guided repair, and held‑out audits. Applied to a second‑hand luxury resale market, the protocol reveals that behavioural parameters are recoverable but calibration is approximate and overconfident for one parameter, and that the simulator’s reachability reference is violated in every cell, particularly in mean purchased tier. The repair improves two of four cells but fails to restore full adequacy, and a held‑out audit uncovers a buyer‑breadth‑dispersion miss not detected earlier; profile‑source ablation shows language‑model‑derived persona profiles outperform a flat rule baseline, though within‑category brand relabelling has no consistent effect. whyItMatters":"The study demonstrates that without an adequacy check, generative social models may appear valid descriptively yet fail to capture key emergent network structures, highlighting the need for rigorous calibration protocols in social simulation research."
arXiv:2606. 10187v1 Announce Type: cross Abstract: We develop a decision-calibrated conformal framework for pacing decisions in streaming advertising.
The paper examines how retail intelligence, which often focuses on high‑velocity products, can suffer from selection bias that skews inflation estimates by overlooking niche items. Using 400 Monte Carlo simulations across four data‑generating scenarios, the authors compare Inverse Probability Weighting (IPW) and stratification methods. They find that stratification generally outperforms IPW—achieving sub‑0.04 percentage‑point median error even when population breaks misalign—while IPW only excels under smooth polynomial relationships, highlighting the importance of method choice in long‑tail retail contexts.
The paper critiques current temporal cascade prediction benchmarks for relying on leakage-prone random splits, limited datasets, and unexamined protocol effects. It proposes a fidelity-aware benchmarking suite featuring the Full Temporal protocol, overlap-based leakage diagnostics, and analyses of performance inflation and temporal drift. Additionally, it introduces the Taoke e‑commerce dataset with rich features and purchase conversions, and presents CasTemp as a lightweight reference method for scalable evaluation.
arXiv:2107. 01629v3 Announce Type: replace-cross Abstract: Livestreaming has evolved into a thriving industry where creators can directly monetize and engage with their audiences and followers.