About Me

I am currently a second-year Master’s student in Computer Science at Northeastern University, focusing on Retrieval-Augmented Generation. Google Scholar:

Now I am engaged in research internships at NEUIR Lab under the guidance of Associate Professor Zhenghao Liu, as well as at THUNLP, supervised by Yukun Yan.

🔎 Research Interests

My research focuses on agentic systems that integrate external knowledge, efficient reasoning, and scalable infrastructure.

• How can models utilize external knowledge: Retrieval-Augmented Generation (RankCoT, GraphAnchor), Deep Research (EigentSearch-Q+), AI Memory.
• How can models reason efficiently: Reasoning Compression (Mixed-Policy Distillation).
• Agent Infrastructure: UltraRAG 2.0.

👀 I am looking for a Ph.D. position starting in Fall 2027 and would love to explore potential collaborations. Let’s connect!

🔥 News

• 2026.04:  🎉 Our paper EigentSearch-Q+ is accepted by ACM CAIS 2026 Demos!
• 2025.08:  🎉 We released UltraRAG 2.0 , an low-code framework for building complex RAG systems!
• 2025.05:  🎉 Our paper RankCoT is accepted by ACL 2025!

📝 Publications

* indicates equal contribution, and † indicates corresponding author.

Arxiv Print

Reasoning Compression with Mixed-Policy Distillation

Han Yang*, Mingyan Wu^*, Bailan He, Zeyu Cao, Sikuan Yan, Kevin Qinghong Lin, Zifeng Ding^*†

📃Paper | 📄PDF

• This work proposes Mixed-Policy Distillation (MPD), a reasoning compression framework that transfers concise reasoning behavior from a larger-sized teacher to a smaller student by distilling teacher-compressed student trajectories. This preserves student-policy exploration while injecting teacher-guided compression.

ACM CAIS 2026 Demos

EigentSearch-Q+: Enhancing Deep Research Agents with Structured Reasoning Tools

Boer Zhang, Mingyan Wu, Dongzhuoran Zhou, Yuqicheng Zhu, Wendong Fan, Puzhen Zhang, Zifeng Ding, Guohao Li, Yuan He^†

📃Paper | 📄PDF |

• This work introduces Q+, a set of query and evidence processing tools that make web search more deliberate by guiding query planning, monitoring search progress, and extracting evidence from long web snapshots.

ACL 2025

RankCoT: Refining Knowledge for Retrieval-Augmented Generation through Ranking Chain-of-Thoughts

Mingyan Wu, Zhenghao Liu^†,Yukun Yan^†, Xinze Li, Shi Yu, Zheni Zeng, Yu Gu, Ge Yu

📃Paper | 📄PDF |

• This work leverages the strengths of both ranking and summarization to effectively refine the knowledge from retrieval results, thereby aiding LLMs in generating more accurate responses.

Arxiv Print

Graph-Anchored Knowledge Indexing for Retrieval-Augmented Generation

Zhenghao Liu^*†, Mingyan Wu^*, Xinze Li, Yukun Yan^†, Shuo Wang, Cheng Yang, Minghe Yu, Zheni Zeng, Maosong Sun

📃Paper | 📄PDF |

• This work reconceptualizes knowledge graphs as dynamically evolving indices that anchor salient entities and relations to guide iterative retrieval and answer generation.

📖 Educations

• 2024.09 - now, M.S. School of Computer Science and Engineering, Northeastern University
• 2020.09 - 2024.07, B.S. School of Computer Science, Yangtze University

💻 Internships

• 2024.04 - now, THUNLP, Tsinghua University, Beijing.
• 2023.10 - now, NEUIR Lab, Northeastern University, Shenyang.

🎼 Amateur

• Dancing 💃: I’ve been danced for about nine years. My favorite dance styles are jazz and hiphop. And I also used to be a part-time dance teacher.
• Guitar 🎸: I am a beginner of guitar and I usually play folk guitar.

• Swimming 🏊: I’ve recently got into swimming and would like to learn more about it.

  If you share these interests, I would be glad to connect and grow together 📞.