arXiv:2608. 10182v1 Announce Type: cross Abstract: Large-scale targeting and recommendation systems are typically built around predictive scores fed into heuristic or local allocation.
arXiv:2607. 14161v1 Announce Type: cross Abstract: Pinterest is where people turn inspiration into action as users browse ideas, then take steps toward realization, often by discovering shoppable content.
arXiv:2605. 15133v2 Announce Type: replace Abstract: Causal inference, estimating causal effects from observational data, is a fundamental tool in many disciplines.
Incentivized advertising allocates monetary or virtual rewards to drive user engagement, where a key challenge is optimizing continuous incentive magnitudes under strict global constraints. This problem is complicated by high-frequency interactions, delayed feedback, and non-Markovian user dynamics such as fatigue, which limit the effectiveness of existing uplift modeling and constrained reinforcement learning approaches.
arXiv:2607. 15577v1 Announce Type: cross Abstract: Causal bandits exploit structural relationships among variables to share information across interventions and accelerate the identification of high-reward decisions.
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:2608. 04421v1 Announce Type: cross Abstract: Incentivized advertising allocates monetary or virtual rewards to drive user engagement, where a key challenge is optimizing continuous incentive magnitudes under strict global constraints.
arXiv:2607. 01104v1 Announce Type: cross Abstract: In Large Language Model (LLM) training, data mixing plays a pivotal role in determining model performance.
arXiv:2602. 08261v2 Announce Type: replace Abstract: Auto-bidding systems strive to maximize marketing value while maintaining high compliance with efficiency constraints, such as Target Cost-Per-Action (CPA).
arXiv:2512. 17629v4 Announce Type: replace-cross Abstract: Prescriptive Process Monitoring (PresPM) recommends interventions during running business processes to optimize key performance indicators (KPIs).
arXiv:2606. 01457v1 Announce Type: new Abstract: Bayesian optimization is a popular way to optimize expensive systems, where every experiment, simulation, or intervention costs time or money.
arXiv:2608. 06792v1 Announce Type: cross Abstract: Foundation model(FM) for recommendation has shown strong ability to model long-horizon sequential user behavior.
arXiv:2607. 20863v1 Announce Type: cross Abstract: Modern recommender systems are typically based on deep learning (DL) models, where a dense encoder learns representations of users and items.