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Mingming Zhang

6 papers hereh-index 16 citations6 works total

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

author position
  • first author5
  • middle author1

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

fields
  • cs.LG3
  • cs.AI2
  • cs.CL1
same name
  • Mingming Zhang — 7 papers, h 8
  • Mingming Zhang — 3 papers, h 27
  • Mingming Zhang — 2 papers, h 4
  • Mingming Zhang — 1 paper, h 5
  • Mingming Zhang — 1 paper, h 1
  • Mingming Zhang — 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
20242026
collaborators
Showing 2026Show all

4 papers · 1 filter

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.CL2026

TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding

Minjie Qiang, Mingming Zhang, Xiaoyi Bao +5

Foundation models have established unified representations for natural language processing, yet this paradigm remains largely unexplored for tabular data. Existing methods face fun…

cs.LG2026

KMLP: A Scalable Hybrid Architecture for Web-Scale Tabular Data Modeling

Mingming Zhang, Pengfei Shi, Zhiqing Xiao +8

Predictive modeling on web-scale tabular data with billions of instances and hundreds of heterogeneous numerical features faces significant scalability challenges. These features e…

cs.LG2026

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

Mingming Zhang, Na Li, Zhuang Feiqing +8

With the rapid development of e-commerce, auto-bidding has become a key asset in optimizing advertising performance under diverse advertiser environments. The current approaches fo…

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