arXiv Machine Learning

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.

arXiv Machine Learning

Jul 22

JD-BP: A Joint-Decision Generative Framework for Auto-Bidding and Pricing

arXiv:2604. 05845v2 Announce Type: replace-cross Abstract: Auto-bidding services optimize real-time bidding strategies for advertisers under key performance indicator (KPI) constraints such as target return on investment and budget.

By Linghui Meng, Chun Gan, Shengsheng Niu, Chengcheng Zhang, Chenchen Li, Chuan Yang, Yi Mao, Xin Zhu, Jie He, Zhangang Lin, Ching Law

reinforcement-learning benchmarks safety

arXiv Machine Learning

Jul 31

PlatformBid: An Auto-Bidding Benchmark from a Unified Advertising Platform's Perspective

arXiv:2607. 27265v1 Announce Type: new Abstract: Real-time bidding is central to computational advertising, comprising three elements: Supply Side Platform (SSP) selling ad impressions, Demand Side Platform (DSP) bidding for advertisers, and Ad Exchange conducting auctions between them.

By Shengtian Yang, Yewen Li, Peng Jiang, Zhiyi Lyu, Bo An, Peng Jiang, Qingpeng Cai, Lei Feng

reinforcement-learning benchmarks

arXiv Machine Learning

1d ago

Learning to Bid with Unknown Private Values in Budget-Constrained First-Price Auctions

arXiv:2605. 09448v2 Announce Type: replace Abstract: We study the operational problem of automated bidding in repeated first-price auctions under budget and return-on-spend (RoS) constraints.

By Zihao Hu, Yuxiao Wen, Yuan Yao, Jiheng Zhang, Zhengyuan Zhou

arXiv Machine Learning

Jun 26

HOB: A Holistically Optimized Bidding Strategy under Heterogeneous Bidding Environments

arXiv:2510. 15238v2 Announce Type: replace-cross Abstract: Optimizing a single advertising campaign across heterogeneous channels is a central challenge in industrial autobidding.

By Qi Li, Wendong Huang, Qichen Ye, Wutong Xu, Cheems Wang, Wei Yuan, Miao Xu, Zhiyu Mou, Guan Wang, Rongquan Bai, Chuan Yu, Jian Xu

benchmarks

arXiv AI

Aug 5

Less Traffic, Better Outcomes: Competition-Aware Request Dispatch in Real-Time Ad Exchanges

arXiv:2608. 03705v1 Announce Type: new Abstract: Real-time bidding (RTB) ad exchanges typically forward nearly all incoming requests to demand-side platforms (DSPs), even though only a small fraction receive bids.

By Jonaid Shianifar, Blaz Mramor, Fangda Zou, Matthieu C. Martin, Xingsheng Guo, Zhihua Zhu, Rong Zhou, Bichen Shi

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.

By Shiwen Shen, Xiru Huang, Liang Luo, Jianbo Sun, He Lyu, Zihang Fu, Ivonne Xu, Zhizhuo Li, Zhengyu Zhang, Pei-Ju Sung, Yunmiao Wang, Zixuan Wang, Zhengli Zhao, Qiang Jin, Mike Jermann, Mingda Li, Yang Xiao, Bhavana Challa, Brooke Bian, Yang Li, Ashish Chamoli, Bibek Bhusal, Danning Di, Yuan Jin, Meet Raval, Zhiwen Chen, Boyao Sun, Shuguang Wang, Yunlong He, Yantao Yao, Sagar Chordia, Wenlin Chen, Santanu Kolay, Qin Huang, Ellie Wen

reinforcement-learning safety

arXiv Machine Learning

Jun 30

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions

arXiv:2606. 28943v1 Announce Type: cross Abstract: Learning to bid in repeated multi-unit auctions with bandit feedback poses a fundamental challenge.

By Junhan Li, Yuxin Zhang, Haoran Wang, Minghao Chen

reinforcement-learning benchmarks safety

arXiv AI

Jul 21

AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization

arXiv:2607. 17281v1 Announce Type: cross Abstract: Auto-bidding plays an essential role in online advertising, automatically adjusting bids for advertisers to optimize their commercial goals.

By Yuejia Dou, Hesong Wang, Xinyu Zhang, Tianyu Wang, Zhilin Zhang, Chuan Yu, Jian Xu, Bo Zheng, Qi Qi

llms agents efficiency safety

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

1d ago

Do LLM Agents Negotiate Rationally? A Mechanism-Design Framework for Verifiable Multi-Agent Interaction over A2A/MCP

arXiv:2608. 14613v1 Announce Type: new Abstract: Modern LLM-agent frameworks increasingly interoperate through standards such as Anthropic's Model Context Protocol (MCP) for agent-to-tool access and Google's Agent2Agent (A2A) protocol for agent delegation and negotiation.

By Wael Albayaydh, Rui Zhao

llms agents benchmarks

arXiv Machine Learning

Jun 15

DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation

arXiv:2606. 14192v1 Announce Type: new Abstract: Auto-bidding is a core component of real-time advertising systems, where decisions must optimize long-term performance under budget and cost constraints, while online exploration is prohibitively risky.

By Miduo Cui, Haochen Wang, Shangqin Mao, Xun Yang, Qianlong Xie, Xingxing Wang, Xuri Ge, Ying Zhou, Zhiwei Xu

llms rag reinforcement-learning benchmarks

arXiv Machine Learning

Jul 8

Contextual Procurement Auctions with Bandit Learning

arXiv:2607. 05813v1 Announce Type: cross Abstract: We study repeated contextual procurement auctions in which the platform must learn context-dependent product values from bandit feedback.

By Yiling Chen, Shi Feng, Sadie Zhao

reinforcement-learning

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