collaborators

5 papers

cs.NI2026

NetCause: Counterfactual Learning for Root Cause Analysis in Large-Scale Networks

Fabien Chraim, Jian Zhang, Dominik Janzing +3

Can a learned model capture how faults propagate through a large-scale network and use this knowledge to causally attribute customer impact to its underlying root cause? Existing r…

cs.CL2026

What Really Matters for Table LLMs? A Meta-Evaluation of Model and Data Effects

Naihao Deng, Sheng Zhang, Henghui Zhu +7

Table modeling has progressed for decades. In this work, we revisit this trajectory and highlight emerging challenges in the LLM era, particularly the paradox of choice: the diffic…

cs.DB2026

An Agentic Approach to Metadata Reasoning

Jiani Zhang, Sercan O. Arik, Cosmin Arad +2

As LLM-driven autonomous agents evolve to perform complex, multi-step tasks that require integrating multiple datasets, the problem of discovering relevant data sources becomes a k…

cs.MA2025

MLZero: A Multi-Agent System for End-to-end Machine Learning Automation

Haoyang Fang, Boran Han, Nick Erickson +10

Existing AutoML systems have advanced the automation of machine learning (ML); however, they still require substantial manual configuration and expert input, particularly when hand…

cs.DB2025

CoddLLM: Empowering Large Language Models for Data Analytics

Jiani Zhang, Hengrui Zhang, Rishav Chakravarti +6

Large Language Models (LLMs) have the potential to revolutionize data analytics by simplifying tasks such as data discovery and SQL query synthesis through natural language interac…