Qian Wang

Qian Wang

CS Ph.D. candidate @ NUS

I am a Computer Science Ph.D. candidate at the National University of Singapore, advised by Prof. Bingsheng He. My research focuses on LLM Multi-Agent Systems, Trustworthy AI, and data-centric approaches to improving foundation models. My research has appeared at top venues including ICLR, NeurIPS, ICML, ACL, EMNLP, COLM, and LOG, as well as in journals such as ACM Computing Surveys and IEEE TKDE, with several Oral presentations. I also received an Outstanding Reviewer Award from EACL 2026.

My representative work, MegaAgent (ACL 2025 Findings), is a fully autonomous large-scale LLM-based multi-agent system that needs no predefined SOPs — it dynamically decomposes tasks, spawns and coordinates agents in parallel, and scales to 590 agents in a national policy simulation.

On the data side, I build pioneering datasets and benchmarks (e.g., EX-Graph at ICLR 2024 and CrossAlpha), and I characterize and mitigate model biases both empirically (judging bias in large reasoning models, COLM 2025) and at training time via reinforcement learning (Treat Bias as Noise). I am also passionate about LLMs for finance: using LLMs to mine cross-market alpha factors from corporate disclosures and to guide trading decisions.

I believe LLMs should be developed and deployed in a way that benefits all of humanity, not just a privileged segment. As a typical ENTP, I’m positive, outgoing, and full of curiosity. I enjoy discussing research, PhD applications, life choices, and beyond — feel free to reach out. I am always open to collaborations: if you share similar interests or see potential synergies, email me at persdre@gmail.com!

📰 News

  • 2026.05 — 📈 New preprint CrossAlpha: an annual-report benchmark for cross-market factor research, covering ~3,600 firms across 5 markets with ~19M firm-pair scores. arXiv
  • 2026.05 — 🎉 4 papers accepted to the ICML 2026 Agents-in-the-Wild Workshop. Looking forward to meeting you in Seoul!
  • 2026.05 — 🏆 Received the Outstanding Reviewer Award from EACL 2026.
  • 2026.05 — 🎯 Treat Bias as Noise (bias-robust LLM reasoning via reinforcement learning, with collaborators from UC Berkeley) was accepted to the ICML 2026 AI4GOOD Workshop. arXiv
  • 2026.04 — 🎉 3 papers accepted to ACL 2026 (incl. Findings).
  • 2026.01 — 🎉 LLM DNA: Tracing Model Evolution via Functional Representations was accepted to ICLR 2026 as an Oral presentation.
  • 2025.10 — 1 paper accepted to LOG 2025 as an Oral presentation.
  • 2025.09 — 🛡️ Towards Evaluating Fake Reasoning Bias in Language Models was accepted to the NeurIPS 2025 Lock-LLM Workshop.
  • 2025.07 — Our paper Assessing Judging Bias in Large Reasoning Models: An Empirical Study was accepted to COLM 2025.
  • 2025.06 — 🤝 Multiple papers accepted to ICML 2025 workshops (incl. the Multi-Agent Systems Workshop), covering multi-agent systems and LLMs for finance.
  • 2025.05 — Our paper MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs was accepted to ACL 2025 Findings.

📝 Selected Publications

Click a topic to filter; my name is shown in bold. The complete list is on my Google Scholar

ACL 2025 Findings ICLR 2025 FM-Wild Workshop Oral MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs Paper Code Qian Wang, T. Wang, Z. Tang, Q. Li, N. Chen, J. Liang, B. He
ICML 2025 Multi-Agent Systems Workshop AgentTaxo: Dissecting and Benchmarking Token Distribution of LLM Multi-Agent Systems Paper Qian Wang, Z. Tang, N. Chen, T. Wang, B. He
ACL 2026 Findings Diversity Collapse in Multi-Agent LLM Systems: Structural Coupling and Collective Failure in Open-Ended Idea Generation N. Chen, Y. Tong, Y. Yang, X. Zhang, Qian Wang, B. He
COLM 2025 Assessing Judging Bias in Large Reasoning Models: An Empirical Study Paper Qian Wang, Z. Lou, Z. Tang, N. Chen, X. Zhao, W. Zhang, D. Song, B. He
NeurIPS 2025 Lock-LLM Workshop Towards Evaluating Fake Reasoning Bias in Language Models Paper Qian Wang, Z. Tang, Z. Lou, N. Chen, W. Wang, B. He
Preprint 2025 JudgeLRM: Large Reasoning Models as a Judge Paper N. Chen, Z. Hu, Q. Zou, J. Wu, Qian Wang, B. Hooi, B. He
ICML 2026 AI4GOOD Workshop Treat Bias as Noise: Training Bias-Robust LLM Reasoning via Reinforcement Learning Paper Qian Wang, X. Zhao, Z. Zhang, Z. Lou, N. Chen, D. Song, B. He
Preprint 2026 Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies Paper Z. Lou, H. Chen, Y. Li, Qian Wang, B. Hooi
Preprint 2026 RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection Paper T. Wang, Z. Ma, Qian Wang, X. Zhang, X. Long, B. Zhou
ICLR 2026 Oral LLM DNA: Tracing Model Evolution via Functional Representations Paper Z. Wu, H. Zhao, Z. Wang, J. Guo, Qian Wang, B. He
Preprint 2026 LLM Agent Memory: A Survey from a Unified Representation–Management Perspective Paper Z. Tang, X. He, T. Zhao, F. Wei, X. Liu, P. Dong, Qian Wang, et al.
ICML 2026 Agents-in-the-Wild Workshop Parameters as Agentic Memory: Internalizing Long-Horizon Memories for Efficient LLM Agents Z. Tang, F. Wei, P. Dong, X. Liu, Qian Wang, X. Chu, B. Li
Preprint 2026 CrossAlpha: An Annual-Report Benchmark for Cross-Market Factor Research Paper Qian Wang, Z. Tong, N. Chen, Z. Wu, B. He
ICLR 2025 Financial AI Workshop Exploring LLM Cryptocurrency Trading Through Fact-Subjectivity Aware Reasoning Paper Code Qian Wang, Y. Gao, Z. Tang, B. Luo, N. Chen, B. He
EMNLP 2024 CryptoTrade: A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading Paper Code Y. Li, B. Luo, Qian Wang, N. Chen, X. Liu, B. He
ICLR 2024 EX-Graph: A Pioneering Dataset Bridging Ethereum and X Paper Code Qian Wang, Z. Zhang, Z. Liu, S. Lu, B. Luo, B. He
LOG 2025 Oral Less is More: Using Buffer Nodes to Reduce Excessive Majority Node Influence in Class Imbalance Graphs Paper Qian Wang, Z. Liu, Z. Zhang, B. Luo, B. He
NeurIPS 2024 Datasets & Benchmarks Multi-Chain Graphs of Graphs: A New Approach to Analyzing Blockchain Datasets Paper B. Luo, Z. Zhang, Qian Wang, B. He
IEEE TKDE 2025 A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions Paper Z. Liu, Y. Li, N. Chen, Qian Wang, B. Hooi, B. He
Preprint 2025 LLM-based Human Simulations Have Not Yet Been Reliable Paper Qian Wang, J. Wu, Z. Tang, B. Luo, N. Chen, W. Chen, B. He
ICLR 2025 Blogposts Can LLM Simulations Truly Reflect Humanity? A Deep Dive Paper Qian Wang, Z. Tang, B. He

🏆 Awards

🎤 Invited Talks & Interviews

  • 2025, Invited talk at Qube Research & Technologies (Singapore office) on leveraging LLMs to make fair and unbiased judgments about factors.
  • 2025, Invited talk at AI4X 2025 on utilizing LLMs to make trading decisions in the cryptocurrency market.
  • 2025, Invited talk on LLM-based human simulations at Renmin University of China, hosted by Yunhai Wang. Slides
  • 2025, Invited talk by AI Time on my ICLR 2025 BlogPost Can LLMs Truly Simulate Humanity? A Deep Dive. Video
  • 2024, Interviewed by the Open Source Promotion Plan (OSPP), a summer program organized by the Institute of Software, Chinese Academy of Sciences. Interview
  • 2023, Invited talk on EX-Graph at The Hong Kong University of Science and Technology (Guangzhou). Slides

📖 Education

  • 2023 - Now, Ph.D. Student, Computer Science, National University of Singapore
  • 2019 - 2022, Bachelor, Computer Science with a Minor in Economics, National University of Singapore
  • 2017 - 2019, Undergraduate, Chemistry, Shanghai Jiao Tong University

💼 Industry Experience

  • 2026.01 - Now, Quant Researcher, MS Capital, Singapore
  • 2022, Algorithm Tutor, OI Wiki, GitHub
  • 2021, Backend Engineer Intern, Ant Group, Shanghai
  • 2020, Python Tutor, InterMine, University of Cambridge

💬 Projects

  • SurviveSJTU Manual: I authored a chapter for the latest edition of the SurviveSJTU Manual — an online survival guide for students at Shanghai Jiao Tong University. You can browse the manual and my contributions on GitHub.

🔥 Service

  • 2025, ICAIF 2025 Secure FinAI Contest Local Organizer
  • 2023 - Now, Seminar Organizer, Xtra Lab, NUS
  • 2023 - Now, Fire Warden, School of Computing, NUS