arXiv Machine Learning

MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction

arXiv:2608. 10562v1 Announce Type: new Abstract: Not all clicks are equal.

arXiv AI

2d ago

AdsWorldEngine: A Self-Evolving Conversational Advertising Agent through Orchestrator and Tool Coevolution

arXiv:2608. 13833v1 Announce Type: cross Abstract: Conversational advertising aims to deliver useful ads within multi-turn assistant interactions.

By Simiao Zuo, Chenhui Xu, Yimeng Jia, Qiang Lou, Jian Jiao, Denis Charles

agents reinforcement-learning fine-tuning

arXiv AI

Jun 16

Attribute Inference from Interactive Targeted Ads

arXiv:2606. 15209v1 Announce Type: new Abstract: Targeted advertising systems can pair audiences selected by advertisers with ad units that expose visible user actions.

By Peihao Li

benchmarks safety

arXiv Machine Learning

Jun 17

Statistical Learning from Attribution Sets

arXiv:2602. 06276v2 Announce Type: replace Abstract: We address the problem of training conversion prediction models in advertising domains under privacy constraints, where direct links between ad clicks and conversions are unavailable.

By Lorne Applebaum, Robert Busa-Fekete, August Y. Chen, Claudio Gentile, Tomer Koren, Aryan Mokhtari

safety

arXiv AI

Jun 19

Bid Farewell to Seesaw: Towards Accurate Long-tail Session-based Recommendation via Dual Constraints of Hybrid Intents

arXiv:2511. 08378v4 Announce Type: replace-cross Abstract: Session-based recommendation (SBR) aims to predict anonymous users' next interaction based on their interaction sessions.

By Xiao Wang, Ke Qin, Dongyang Zhang, Xiurui Xie, Shuang Liang

benchmarks

arXiv Machine Learning

Aug 4

LLM-OSDA: An Optimal-Stopping Dynamic Auction for Native Advertising in Multi-Turn LLM Conversations

arXiv:2608. 00123v1 Announce Type: cross Abstract: LLM-native advertising embeds sponsored content directly into model-generated responses, shifting the unit of sale from a fixed slot to a moment within an evolving conversation.

By Yan Fang, Jialin Chen, Chun Gan, Hang Yu, Mingjun Nie, Yeyu Zhang, Fengxiang He, Ching Law

llms

arXiv Machine Learning

Jun 2

Jointly Optimizing Debiased CTR and Uplift for Coupons Marketing: A Unified Causal Framework

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

safety

arXiv AI

Jun 26

From Clicks to Intent: Cross-Platform Session Embeddings with LLM-Distilled Taxonomy for Financial Services Recommendations

arXiv:2606. 26277v1 Announce Type: cross Abstract: Sequential user behavior modeling is widely adopted in industrial recommender systems; however, significant gaps remain in financial services, where pre-login web interactions and authenticated in-app experiences differ drastically.

By Dianjing Fan, Yao Li, Kyaw Hpone Myint, Dwipam Katariya, Alexandre G. R. Day, Pranab Mohanty, Giri Iyengar

llms rag efficiency multimodal

arXiv Machine Learning

Aug 12

CADET: Context-Conditioned Ads CTR Prediction With a Decoder-Only Transformer

arXiv:2602. 11410v2 Announce Type: replace Abstract: Click-through rate (CTR) prediction is fundamental to online advertising systems.

By David Pardoe, Neil Daftary, Miro Furtado, Aditya Aiyer, Yu Wang, Liuqing Li, Tao Song, Lars Hertel, Young Jin Yun, Senthil Radhakrishnan, Zhiwei Wang, Tommy Li, Khai Tran, Ananth Nagarajan, Ali Naqvi, Yue Zhang, Renpeng Fang, Avi Romascanu, Arjun Kulothungun, Deepak Kumar, Praneeth Boda, Fedor Borisyuk, Ruoyan Wang

llms rag efficiency

arXiv Machine Learning

5d ago

Doubly Robust Estimation of Causal Effect on CVR with Targeted Regularization

arXiv:2608. 13461v1 Announce Type: new Abstract: Post-click conversion rate (CVR) is a key metric in various scenarios including e-commerce and advertising, reflecting the efficiency and user experience in the second stage of the conversion process.

By Jiayi Dan, Bo Li, Lu Deng, Yong Wang

safety

arXiv Machine Learning

Jul 17

Adaptive Ad Load Design for Sponsored Search Markets: Evidence, Theory, and Deployment

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.

By Mohammad Rashid, Hema Yoganarasimhan

benchmarks

arXiv AI

1d ago

Dear Algo: A Precision-First Agentic Intent Layer for Unified Search and Recommendation

arXiv:2608. 15877v1 Announce Type: new Abstract: Search and recommendation serve a shared discovery objective but encode intent differently.

By Rui Wang, Jiazhou Wang, Zheng Wei, Chenglin Lu, Fangcheng Sun, Ivy Sun, Jin Sun, Hui Geng, Lillian Zhang, Chao Yang, Lei Chen, Shahin Sefati, Reem Helou, Joe Zhou, Babak Shakibi, Yiyi Pan, Bi Xue, Hong Yan, Shujian Bu

llms rag agents multimodal

arXiv Machine Learning

Jul 28

Uncertainty Modeling for Multi-Objective RTA Interception with Distillation Acceleration

arXiv:2511. 05582v3 Announce Type: replace Abstract: Real-Time Auction (RTA) interception decides which incoming advertising requests reach downstream systems, and therefore controls the quality of the data those systems learn from.

By Gaoxiang Zhao, Ruinan Qiu, Xiaoting Wang, Pengpeng Zhao, Rongjin Wang, Xiaoting Wang, Zhangang Lin, Xiaoqiang Wang

efficiency

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