arXiv AI
Jun 10
Atomic Intent Reasoning: Bringing LLM Semantics to Industrial Cross-Domain Recommendations
arXiv:2606. 10357v1 Announce Type: cross Abstract: Cross-domain recommendation is a core problem in content-to-e-commerce platforms.
Can Large Language Models Identify Meaningful Touchpoints in Conversion Attribution?
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arXiv AI
Jun 8
Re-Centering Humans in LLM Personalization
arXiv:2606. 06614v1 Announce Type: cross Abstract: Despite growing interest, most evaluations of large language models' (LLMs') personalization abilities have relied on synthetic data.
arXiv AI
Jul 7
Enhancement of E-commerce Sponsored Search Relevancy with LLM
arXiv:2607. 03886v1 Announce Type: cross Abstract: Sponsored search plays a crucial role as a revenue stream for search engines, wherein advertisers competitively bid on keywords that align with the users' search queries.
arXiv AI
Aug 10
MAC: A Conversion Rate Prediction Benchmark Featuring Labels Under Multiple Attribution Mechanisms
arXiv:2603. 02184v2 Announce Type: replace-cross Abstract: Multi-attribution learning (MAL), which enhances model performance by learning from conversion labels yielded by multiple attribution mechanisms, has emerged as a promising learning paradigm for conversion rate (CVR) prediction.
arXiv AI
Sep 1
Evaluating the Hidden Costs of Personalization in Large Language Models
arXiv:2608.28833v1 Announce Type: new Abstract: While Large language models (LLMs) incorporate user personalization signals to improve usability and helpfulness, they increasingly shift from providin...
arXiv Machine Learning
Jul 28
SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads
arXiv:2607. 23121v1 Announce Type: cross Abstract: Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-surfacing known interests) and prospecting (discovering new categories).
arXiv AI
Aug 13
From Prompting to Behavioral Alignment: Personalized LLM Judges for Recommendation Evaluation
arXiv:2608. 11493v1 Announce Type: new Abstract: Traditional offline recommendation evaluation relies heavily on complex, manually maintained feature pipelines that are difficult to scale.
arXiv AI
Jun 2
Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems
arXiv:2606. 00282v1 Announce Type: cross Abstract: Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback.
arXiv AI
Jun 3
Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation
arXiv:2606. 03866v1 Announce Type: cross Abstract: Scaling recommender systems via large language models (LLMs) has become a prominent trend in the industry.
arXiv Machine Learning
Jul 31
Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models
arXiv:2607. 27421v1 Announce Type: cross Abstract: Intent classification is a core component of task-oriented dialogue systems, yet practitioners have limited systematic guidance for selecting deployable open-weight language models under compute, latency, and robustness constraints.
arXiv AI
Aug 26
Ad Insertion in LLM-Generated Responses
arXiv:2601.19435v2 Announce Type: replace-cross Abstract: Sustainable monetization of large language models (LLMs) remains a critical open challenge. Traditional search advertising, which relies on s...
arXiv Machine Learning
Aug 12
MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction
arXiv:2608. 10562v1 Announce Type: new Abstract: Not all clicks are equal.