Ze Wang
Scholar

Ze Wang

Google Scholar ID: M6GT5AsAAAAJ
University College London
Existential Risk from AI
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
43
 
H-index
3
 
i10-index
2
 
Publications
4
 
Co-authors
0
 
Contact
CVOpen ↗
Publications
3 items
Tool Calling is Linearly Readable and Steerable in Language Models
2026
Cited
0
AI Alignment Amplifies the Role of Race, Gender, and Disability in Hiring Decisions
arXiv.org · 2026
Cited
0
NormCode Canvas: Making LLM Agentic Workflows Development Sustainable via Case-Based Reasoning
2026
Cited
0
Resume
Academic Achievements
  • Publications:
  • - Bias Amplification: Large Language Models as Increasingly Biased Media, International Joint Conference on Natural Language Processing & Asia-Pacific Chapter of the Association for Computational Linguistics, 2025
  • - SAGED: A Holistic Bias-Benchmarking Pipeline for Language Models with Customisable Fairness Calibration, Proceedings of the 31st International Conference on Computational Linguistics
  • - JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models, Findings of the Association for Computational Linguistics: EMNLP 2024
  • Work in progress:
  • - Large Language Models in Hiring
  • - Bargaining game with reference-dependent preferences
  • - How does breastfeeding influence infant mortality? Insights from India
Background
  • PhD Candidate in the Department of Economics at University College London and a PhD Scholar at the Stone Centre. My research is on existential risk from AI and science for AI.