Scholar
Yuchen Zeng
Google Scholar ID: vex4iuYAAAAJ
Microsoft Research
Citations & Impact
Citations
522
H-index
7
i10-index
6
Publications
13
Co-authors
11
list available
Publications
Resume (English only)
Academic Achievements
- ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning (Under Review)
- DARWIN 1.5: Large Language Models as Materials Science Adapted Learners (Under Review)
- State-offset Tuning: State-based Parameter-Efficient Fine-Tuning for State Space Models (ACL 2025)
- TabFlex: Scaling Tabular Learning to Millions with Linear Attention (ICML 2025 Spotlight)
- Parameter-Efficient Fine-Tuning of State Space Models (ICML 2025)
- Can MLLMs Perform Text-to-Image In-Context Learning? (COLM 2024)
- The Expressive Power of Low-Rank Adaptation (ICLR 2024)
- LIFT: Language-Interfaced FineTuning for Non-Language Machine Learning Tasks (NeurIPS 2022)
- Federated Learning with Local Fairness Constraints (ISIT 2023)
- Equal Improvability: A New Fairness Notion Considering the Long-Term Impact (ICLR 2023)
- Multiway clustering via tensor block models (NeurIPS 2019)
Background
- A Senior Researcher at Microsoft Research AI Frontiers, working with Prof. Dimitris Papailiopoulos. Research interests include deep learning, foundation models, and machine learning fairness.
