activity
20202026
most citedA Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising

24 citations · 37 across the 20 of their papers we have counts for

collaborators

22 papers

cs.LG2026

Learning Deployable Causal Action Geometry under Temporal Non-Stationarity

Changjian Liu, Tianyu Wang, Yuwei Xu +6

Learning a response law for continuous decisions from observational time series is central to many real-world decision systems, yet temporal non-stationarity poses a fundamental ch…

cs.LG2026

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

Yuejia Dou, Hesong Wang, Xinyu Zhang +6

Auto-bidding plays an essential role in online advertising, automatically adjusting bids for advertisers to optimize their commercial goals. The emerging AI-Generated Bidding (AIGB…

cs.IR2026

LERA: LLM-Enhanced RAG for Ad Auction in Generative Chatbots

Haoran Sun, Xinrui Song, Xinyu Zhang +7

The integration of advertising auction mechanisms into large language model (LLM)-based chatbots presents a significant opportunity for commercialization, yet poses unique challeng…

cs.LG2026

Smartwatch-Based Sitting Time Estimation in Real-World Office Settings

Olivia Zhang, Zhilin Zhang

Sedentary behavior poses a major public health risk, being strongly linked to obesity, cardiovascular disease, and other chronic conditions. Accurately estimating sitting time is t…

cs.AI2026

DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs

Mingxuan Song, Yusen Huo, Bohan Zhou +5

Optimizing the advertiser's cumulative value of winning impressions under budget constraints poses a complex challenge in online advertising, under the paradigm of AI-Generated Bid…

cs.AI2025

Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens

Jiahao Ji, Tianyu Wang, Yeshu Li +5

Auto-bidding is crucial in facilitating online advertising by automatically providing bids for advertisers. While previous work has made great efforts to model bidding environments…

cs.GT2025★ 2 cited

Beyond Advertising: Mechanism Design for Platform-Wide Marketing Service "QuanZhanTui"

Ningyuan Li, Zhilin Zhang, Tianyan Long +8

On e-commerce platforms, sellers typically bid for impressions from ad traffic to promote their products. However, for most sellers, the majority of their sales come from organic t…

cs.GT2025

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

Zhijian Duan, Yusen Huo, Tianyu Wang +6

In online advertising, advertisers commonly utilize auto-bidding services to bid for impression opportunities. A typical objective of the auto-bidder is to optimize the advertiser'…

cs.AI2024★ 3 cited

AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games

Kefan Su, Yusen Huo, Zhilin Zhang +5

Decision-making in large-scale games is an essential research area in artificial intelligence (AI) with significant real-world impact. However, the limited access to realistic larg…

cs.LG2024★ 2 cited

AIGB: Generative Auto-bidding via Conditional Diffusion Modeling

Jiayan Guo, Yusen Huo, Zhilin Zhang +5

Auto-bidding plays a crucial role in facilitating online advertising by automatically providing bids for advertisers. Reinforcement learning (RL) has gained popularity for auto-bid…

cs.GT2024

MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising

Zhen Gong, Lvyin Niu, Yang Zhao +9

Online bidding and auction are crucial aspects of the online advertising industry. Conventionally, there is only one slot for ad display and most current studies focus on it. Nowad…

cs.LG2024

Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding

Haoming Li, Yusen Huo, Shuai Dou +5

In online advertising, advertisers participate in ad auctions to acquire ad opportunities, often by utilizing auto-bidding tools provided by demand-side platforms (DSPs). The curre…

cs.GT2024

Automated Deterministic Auction Design with Objective Decomposition

Zhijian Duan, Haoran Sun, Yichong Xia +6

Identifying high-revenue mechanisms that are both dominant strategy incentive compatible (DSIC) and individually rational (IR) is a fundamental challenge in auction design. While t…

cs.GT2023

Learning against Non-credible Auctions

Qian Wang, Xuanzhi Xia, Zongjun Yang +7

The standard framework of online bidding algorithm design assumes that the seller commits himself to faithfully implementing the rules of the adopted auction. However, the seller m…

cs.GT2023★ 1 cited

Truthful Auctions for Automated Bidding in Online Advertising

Yidan Xing, Zhilin Zhang, Zhenzhe Zheng +4

Automated bidding, an emerging intelligent decision making paradigm powered by machine learning, has become popular in online advertising. Advertisers in automated bidding evaluate…

cs.GT2022

Utility Maximizer or Value Maximizer: Mechanism Design for Mixed Bidders in Online Advertising

Hongtao Lv, Zhilin Zhang, Zhenzhe Zheng +5

Digital advertising constitutes one of the main revenue sources for online platforms. In recent years, some advertisers tend to adopt auto-bidding tools to facilitate advertising p…

cs.GT2022

Learning Optimal Deterministic Auctions with Correlated Valuation Distributions

Da Huo, Zhilin Zhang, Zhenzhe Zheng +3

In mechanism design, it is challenging to design the optimal auction with correlated values in general settings. Although value distribution can be further exploited to improve rev…

cs.GT2021★ 1 cited

On Designing a Two-stage Auction for Online Advertising

Yiqing Wang, Xiangyu Liu, Zhenzhe Zheng +4

For the scalability of industrial online advertising systems, a two-stage auction architecture is widely used to enable efficient ad allocation on a large set of corpus within a li…

cs.GT2021★ 3 cited

Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising

Xiangyu Liu, Chuan Yu, Zhilin Zhang +10

In e-commerce advertising, it is crucial to jointly consider various performance metrics, e.g., user experience, advertiser utility, and platform revenue. Traditional auction mecha…

cs.MA2021★ 24 cited

A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising

Chao Wen, Miao Xu, Zhilin Zhang +12

In online advertising, auto-bidding has become an essential tool for advertisers to optimize their preferred ad performance metrics by simply expressing high-level campaign objecti…

cs.GT2021

Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising

Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng +7

In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform…

physics.flu-dyn2020★ 1 cited

A novel control mode of bionic morphing tail based on deep reinforcement learning

Liming Zheng, Zhou Zhou, Pengbo Sun +2

In the field of fixed wing aircraft, many morphing technologies have been applied to the wing, such as adaptive airfoil, variable span aircraft, variable swept angle aircraft, etc.…