About Me
Hi 👋, I am Yuan Tian. I'm currently a Ph.D. candidate in the Department of Computer Science at Purdue University, advised by Professor Tianyi Zhang.
My research spans machine learning, natural language processing, and human-computer interaction.
During my PhD, I'm applying grounding
theory and anchoring
effect to make generative AI more controllable and accurate, with a particular focus on
code generation __
I'm broadly interested in advancing AI across all dimensions, such as designing effective architecture &
reasoning pipeline, creating high-quality training & evaluation data, or soliciting human feedback via
efficient interaction design.
My ultimate objective is to increase the earth intelligence (humanity + machine) as a whole.
I interned twice at
Adobe
as an applied scientist, where I mainly worked on building the
AI assistant for Adobe
Experience Platform. Meanwhile,
I am part of an
NSF project
(Prototype
Open Knowledge Network), focused on secure chains for LLMs.
📢 I am actively seeking full-time research positions related to generative AI. If you happen to know of any opportunities, I would greatly appreciate it if you could share them with me (tian211@purdue.edu). Thank you!
Publications
Selective Prompt Anchoring for Code Generation
Yuan Tian, Tianyi Zhang
Proceedings of International Conference on Machine Learning
HuggingFace
AGENTPbD: Interactive Agentic Workflow Generation from User Demonstration on Web Browsers
Jiawen Li, Zheng Ning, Yuan Tian, Toby Jia-Jun Li
The IEEE Symposium on Visual Languages and Human-Centric Computing
Insights into Natural Language Database Query Errors: From Attention Misalignment to User Handling Strategies
Zheng Ning*, Yuan Tian*, Zheng Zhang, Tianyi Zhang, Toby Jia-Jun Li
* Equal Contribution
ACM Transactions on Interactive Intelligent Systems
Interactive Text-to-SQL Generation via Editable Step-by-Step Explanations
Yuan Tian, Zheng Zhang, Zheng Ning, Toby Jia-Jun Li, Jonathan K. Kummerfeld, Tianyi Zhang
Proceedings of Conference on Empirical Methods in Natural Language Processing
An Empirical Study of Model Errors and User Error Discovery and Repair Strategies in Natural Language Database Queries
Zheng Ning*, Zheng Zhang*, Tianyi Sun, Yuan Tian, Tianyi Zhang, and Toby Jia-Jun Li
Proceedings of ACM Conference on Intelligent User Interfaces
Preprints
Ask More, Score Higher: Towards Robust Semantic Enrichment through Interactive Query Population and Richness Scoring
Yuan Tian, Yiru Chen, Rakesh R. Menon, Zifan Liu, Ting Cai, Fei Wu, Anudeep Chimakurthi, Prashanthi Ramamurthy, Sridevi Aishwariya Ganesan, Kun Qian, Yunyao Li
ISEE: Interactive Semantic Enrichment for Data Field Description
Yuan Tian, Yiru Chen, Rakesh R. Menon, Zifan Liu, Ting Cai, Fei Wu, Anudeep Chimakurthi, Prashanthi Ramamurthy, Sridevi Aishwariya Ganesan, Kun Qian, Yunyao Li
Alloy: Generating Reusable Agent Workflows from User Demonstration
Jiawen Li, Zheng Ning, Yuan Tian, Toby Jia-Jun Li
TACO: Task-Aware Column Description Generation Using Large Language Models
Ting Cai, Yiru Chen, Rakesh R. Menon, Zifan Liu, Yuan Tian, Fei Wu, Anudeep Chimakurthi, Prashanthi Ramamurthy, Sridevi Aishwariya Ganesan, Kun Qian, Yunyao Li
Encountered-Type Haptic Display via Tracking Calibrated Robot
Chenxi Xiao*, Yuan Tian*
* Equal Contribution
Supporting Construction Worker Well-Being with a Multi-Agent Conversational AI System
Fan Yang, Yuan Tian, Jiansong Zhang
Self-Anchor: Large Language Model Reasoning via Step-by-step Attention Alignment
Hongxiang Zhang, Yuan Tian, Tianyi Zhang
