collaborators

7 papers

cs.AI2026

Nonuniformity Principle in Human-AI Coworking

An Luo, Jie Ding

As generative AI is increasingly applied to automate multi-step and high-stake workflows, human judgment and involvement remain essential for ensuring the quality of AI-generated o…

cs.LG2026

AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science

An Luo, Jin Du, Xun Xian +12

Data science plays a critical role in transforming complex data into actionable insights across numerous domains. Recent developments in large language models (LLMs) and artificial…

cs.AI2026

Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference

Jin Du, Li Chen, Xun Xian +6

Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it remains unclear whether large language mod…

stat.ML2026

ADD for Multi-Bit Image Watermarking

An Luo, Jie Ding

As generative models enable rapid creation of high-fidelity images, societal concerns about misinformation and authenticity have intensified. A promising remedy is multi-bit image…

cs.LG2025

Can Agentic AI Match the Performance of Human Data Scientists?

An Luo, Jin Du, Fangqiao Tian +9

Data science plays a critical role in transforming complex data into actionable insights across numerous domains. Recent developments in large language models (LLMs) have significa…

cs.LG2025

AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science

An Luo, Xun Xian, Jin Du +12

Large language models (LLMs) have advanced the automation of data science workflows. Yet it remains unclear whether they can critically leverage external domain knowledge as human…