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Fei Xiao

6 papers hereh-index 1117 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.IR3
  • cs.AI1
  • cs.LG1
  • stat.ML1
same name
  • Fei Xiao — 7 papers, h 5
  • Fei Xiao — 3 papers, h 2
  • Fei Xiao — 3 papers, h 3
  • Fei Xiao — 3 papers, h 10
  • Fei Xiao — 1 paper, h 2
  • Fei Xiao — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedCascade Ranking for Operational E-commerce Search

111 citations · 112 across the 6 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.LG2026

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

Chennan Ma, Yanning Zhang, Siqi Hong +3

Traditional dynamic pricing models in large-scale e-commerce suffer from limited interpretability, poor utilization of unstructured information, and misalignment with long-term bus…

cs.AI2026

Generative Auto-Bidding with Unified Modeling and Exploration

Mingming Zhang, Feiqing Zhuang, Na Li +7

Automated bidding is central to modern digital advertising. Early rule-based methods lacked adaptability, while subsequent Reinforcement Learning approaches modeled bidding as a Ma…

cs.IR2026

Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search

Yifan Wang, Yixuan Wang, YiDan Liang +2

New item growth is critical for maintaining a healthy ecosystem in large-scale e-commerce platforms. However, existing systems tend to prioritize presenting users with already popu…

cs.IR2026

IDProxy: CTR Prediction with Multimodal LLMs for Cold-Start Recommendation at Xiaohongshu

Yubin Zhang, Haiming Xu, Guillaume Salha-Galvan +6

Content-driven platforms such as Xiaohongshu often leverage click-through rate (CTR) prediction models for recommendation. However, these models depend heavily on item ID embedding…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.