arXiv AI

AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing

arXiv:2606. 26787v1 Announce Type: cross Abstract: Traditional dynamic pricing models in large-scale e-commerce suffer from limited interpretability, poor utilization of unstructured information, and misalignment with long-term business objectives such as cumulative Gross Merchandise Value (GMV), Return on Investment (ROI) and milestone achievement.

arXiv AI

Jul 7

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance

arXiv:2510. 08048v4 Announce Type: replace-cross Abstract: Query-product relevance prediction is fundamental to e-commerce search and has become even more critical in the era of AI-powered shopping, where semantic understanding and complex reasoning directly shape the user experience and business conversion.

By Jianhui Yang, Yiming Jin, Pengkun Jiao, Chenhe Dong, Zerui Huang, Shaowei Yao, Xiaojiang Zhou, Dan Ou, Haihong Tang

llms reinforcement-learning fine-tuning

arXiv AI

Jun 4

Rethinking Sales Lead Scoring with LLM-based Hierarchical Preference Ranking

arXiv:2606. 04387v1 Announce Type: cross Abstract: Sales lead conversion in high-stakes domains (e.

By Chenyu Zhang, Yiwen Liu, Yin Sun, Xinyuan Zhang, Yuji Cao, Junming Jiao, Juyi Qiao

llms 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 Machine Learning

Jun 15

High-Frequency Pricing at Scale for E-Commerce

arXiv:2606. 13741v1 Announce Type: new Abstract: This paper presents the design, development, and implementation of a specialized forecast-then-optimize algorithmic pricing tool for sales campaigns in fashion e-commerce.

By Stefan Birr, Tobias Huelden, Mones Raslan, Adele Gouttes, Andreas Schmitt, Mateusz Koren, Johannes Stephan, Robert Streek, Manuel Kunz, Tim Januschowski

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 AI

Jul 24

SalesLoop: Reinforcement Learning from Performance Feedback for Sales Lead Ranking

arXiv:2607. 20655v1 Announce Type: cross Abstract: Lead ranking in Customer Relationship Management (CRM) systems faces a persistent challenge: models achieving high offline accuracy often underperform in production.

By Chenyu Zhang

reinforcement-learning

arXiv Machine Learning

1d ago

PRO-Bid: Pareto-Prioritized Regret Optimization for Constraint-Aware Generative Auto-Bidding

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).

By Binglin Wu, Yingyi Zhang, Xianneng Li, Ruyue Deng, Chuan Yue, Weiru Zhang, Xiaoyi Zeng

llms benchmarks

arXiv Machine Learning

Jul 31

FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning

arXiv:2607. 28127v1 Announce Type: cross Abstract: Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs).

By Giorgos Iacovides, Wuyang Zhou, Danilo Mandic

llms nlp reinforcement-learning benchmarks

arXiv AI

1d ago

Leveraging Machine Unlearning for Cost-Efficient Preference Alignment

arXiv:2504. 06659v2 Announce Type: replace-cross Abstract: Despite advances in Preference Alignment (PA) for Large Language Models (LLMs), mainstream methods like reinforcement learning with human feedback face notable challenges.

By Xiaohua Feng, Yuyuan Li, Huwei Ji, Jiaming Zhang, Li Zhang, Tianyu Du, Chaochao Chen

llms reinforcement-learning safety

arXiv AI

Jun 8

InvEvolve: Evolving White-Box Inventory Policies via Large Language Models with Performance Guarantees

arXiv:2605. 00369v4 Announce Type: replace-cross Abstract: We study how large language models can be used to generate inventory policies in online settings with non-stationary demand.

By Chenyu Huang, Jianghao Lin, Zhengyang Tang, Bo Jiang, Ruoqing Jiang, Benyou Wang, Lai Wei

llms reinforcement-learning benchmarks safety

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.

By Yuecheng Li, Zeyu Song, Jing Yao, Chi Lu, Peng Jiang, Kun Gai

llms reinforcement-learning fine-tuning safety

arXiv AI

1d ago

Q-Regularized Generative Auto-Bidding: From Suboptimal Trajectories to Optimal Policies

arXiv:2601. 02754v3 Announce Type: replace-cross Abstract: With the rapid development of e-commerce, auto-bidding has become a key asset in optimizing advertising performance under diverse advertiser environments.

By Mingming Zhang, Na Li, Zhuang Feiqing, Hongyang Zheng, Jiangbing Zhou, Wang Wuyin, Sheng-jie Sun, XiaoWei Chen, Junxiong Zhu, Lixin Zou, Chenliang Li

llms reinforcement-learning benchmarks

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