Rikiya Takehi
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I am interested in Machine Learning (ML), Natural Language Processing (NLP), and Information Retrieval (IR). Now, I am especially interested in designing better LLMs / LLM Systems / LLM Agents.
I am a first-year PhD student at MIT CSAIL, advised by Prof. Omar Khattab. I recently received a B.Eng. from Waseda University, where I was supervised by Prof. Tetsuya Sakai. Previously, I was a research intern at NVIDIA Research, focusing on AI agents. Before that, I was a guest researcher at NIST working with Dr. Ian Soboroff and Dr. Ellen Voorhees, and I have also collaborated with Prof. Fernando Diaz of CMU LTI on retrieval rankings.
My first two years of graduate studies are funded by the Toyota PhD Fellowship.
News
- Mar.2026: Graduated from Waseda University as the representative recipient of the Ono Azusa Award, Waseda University's highest honour award, selected as 1 student out of 10,000+ science and engineering students including graduate students (top 0.01%).
- Mar.2026: Started a research internship at NVIDIA Research, focusing on AI agents.
- Feb.2026: First-authored full paper Diversification as Risk Minimization received the WSDM 2026 Best Paper Award.
- Feb.2026: Our Hugging Face ColBERT models mxbai-edge-colbert-v0-17m and mxbai-edge-colbert-v0-32m surpassed 3M+ downloads in total.
- Jan.2026: Co-first-authored full paper Retention-Driven Two-Sided Matching got accepted to ICLR 2026.
- Oct.2025: First authored full paper Diversity as Risk Minimization got accepted to WSDM 2026.
- Oct.2025: Released two open-source ColBERT models mxbai-edge-colbert-v0-17m and mxbai-edge-colbert-v0-32m. Tech report here.
- Aug.2025: My co-authored paper got accepted to CIKM 2025.
- Aug.2025: Started research internship at Mixedbread.
- Jul.2025: Selected as a Toyota PhD Fellow: 2 yrs of full funding.
- Jul.2025: Gave an invited talk (w/ Prof. ChengXiang Zhai) at SIGIR 2025 eCOM Workshop invited by Dr. Tracy Holloway King.
- Jun.2025: Invited as a panelist at NTCIR 2025 with Prof. Maarten De Rijke, Prof. Mark Sanderson, Prof. Charles Clarke, & Prof. Ian Soboroff.
- Jun.2025: Gave an invited talk at EVIA 2025 about Using LLMs as Assistants for Building Test Collections invited by Prof. Charles Clarke, Prof. Noriko Kando, & Prof. Makoto Kato. Slides can be found here.
- Apr.2025: First authored full paper LLM-Assisted Relevance Assessments: When Should We Ask LLMs for Help? got accepted to SIGIR 2025!!
- Jan.2025: First authored full paper General Framework for Off-Policy Learning with Partially-Observed Reward got accepted to ICLR 2025.
- Nov.2024: Gave an invited talk at NII about Using LLMs as Assistants for Building Test Collections invited by Prof. Noriko Kando.
- Nov.2024: First authored paper LLM-Assisted Relevance Assessments: When Should We Ask LLMs for Help? preprint available on arXiv.
- Oct.2024: Started research internship at CyberAgent AI Lab. Algorithm Team.
- Aug.2024: Gave an invited talk at UMD College Park about Nugget-Based Evaluation and the Use of LLMs invited by Prof. Douglas Oard.
- Oct.2023: First-authored paper Open-Domain Dialogue Quality Evaluation: Deriving Nugget-level Scores from Turn-level Scores accepted to SIGIR AP 2023.
Publications
You can also find my articles on my Google Scholar profile.
- Diversification as Risk Minimization
Rikiya Takehi, Fernando Diaz, Tetsuya Sakai. 2025.
WSDM 2026.
Best Paper Award (top 0.1%, 1 of 799 submissions)
arXiv - Beyond Match Maximization and Fairness: Retention-Objectified Two-Sided Matching
Rikiya Takehi*, Ren Kishimoto*, Koichi Tanaka, Masahiro Nomura, Riku Togashi, Yuta Saito. 2025.
ICLR 2026.
preprint - Fantastic (small) Retrievers and How to Train Them: mxbai-edge-colbert-v0 Tech Report.
Rikiya Takehi, Benjamin Clavié, Sean Lee, Aamir Shakir. 2025.
Tech Report.
3M+ downloads on Hugging Face
Tech Report | Blog | 17M ColBERT model | 32M ColBERT model - General Framework for Off-Policy Learning with Partially-Observed Reward
Rikiya Takehi, Kosuke Kawakami, Masahiro Asami, Yuta Saito. 2025.
ICLR 2025.
arXiv | OpenReview | presentation | poster - LLM-Assisted Relevance Assessments: When Should We Ask LLMs for Help?
Rikiya Takehi, Ellen M. Voorhees, Tetsuya Sakai, and Ian Soboroff. 2025.
SIGIR 2025.
arXiv | slides | code - Open-Source LLM-based Relevance Assessment vs. Highly Reliable Manual Relevance Assessment: A Case Study
Tetsuya Sakai, Khant Myoe Rain, Rikiya Takehi, Sijie Tao, Youngin Song. 2025.
CIKM 2025.
proceedings - Objective-driven Calibrated Recommendations
Rikiya Takehi*, Koichi Tanaka*, Ren Kishimoto, Masahiro Nomura, Riku Togashi, Yuta Saito. 2025.
preprint - Open-Domain Dialogue Quality Evaluation: Deriving Nugget-level Scores from Turn-level Scores
Rikiya Takehi, Akihisa Watanabe, and Tetsuya Sakai. 2023.
SIGIR-AP 2023.
code | poster | slides | proceedings
Experience
- Research Intern, NVIDIA Research
- Research Intern, Mixedbread
- Research Intern, CyberAgent AI Lab. Algorithm Team
- Research Intern, Hakuhodo Tech Inc.
- Guest Researcher, NIST Retrieval Group
Achievements
Awarded to PhD students with exemplary academic and research achievements and great promise for future accomplishments.
Graduated as the representative recipient of the Ono Azusa Award, selected as 1 student out of 10,000+ science and engineering students including graduate students (top 0.01%).
Diversification as Risk Minimization received the Best Paper Award (1 of 799 submissions).
Selected as a Toyota PhD Fellow, with my first two years of graduate studies fully funded.
Selected Invited Talks
- Cornell UniversityDiversification as Risk Minimization
- SIGIR eCom Workshop 2025Product Search and Recommendations (with Prof. ChengXiang Zhai)
- EVIA 2025Using LLMs as Assistants for Building Large Test Collections
- University of Maryland, College ParkNugget-Based Evaluation and the Use of LLMs
- NTCIR 2025 PanelistWith Profs. Maarten de Rijke (UvA), Mark Sanderson (RMIT), Charles Clarke (UWaterloo), and Ian Soboroff (NIST).