29 citations · 32 across the 7 of their papers we have counts for
10 papers
Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models
Yurong Liu, Yeye He, Haoyu Dong +4
Predicting missing cell values in tabular data is a fundamental problem in data cleaning. While state-of-the-art reasoning models show great promise in predicting missing values in…
AgentTrails: Towards Trust and Reuse for Agentic Tasks
Eden Wu, Sonia Castelo, Yurong Liu +2
LLM-powered agents increasingly tackle complex tasks by invoking tools, querying databases, executing code, and manipulating intermediate artifacts. These agents follow trajectorie…
LakeQA: An Exploratory QA Benchmark over a Million-Scale Data Lake
Haonan Wang, Jiaxiang Liu, Yurong Liu +11
Recent large language models (LLMs) have shown rapid progress in reading-based question answering (QA), where evidence is explicitly provided or can be trivially retrieved. In cont…
BDI-Kit Demo: A Toolkit for Programmable and Conversational Data Harmonization
Roque Lopez, Yurong Liu, Christos Koutras +1
Data harmonization remains a major bottleneck for integrative analysis due to heterogeneity in schemas, value representations, and domain-specific conventions. BDI-Kit provides an…
Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
R. Teal Witter, Yurong Liu, Christopher Musco
With origins in game theory, probabilistic values like Shapley values, Banzhaf values, and semi-values have emerged as a central tool in explainable AI. They are used for feature a…
AutoDDG: Automated Dataset Description Generation using Large Language Models
Haoxiang Zhang, Yurong Liu, Aécio Santos +2
The proliferation of datasets across open data portals and enterprise data lakes presents an opportunity for deriving data-driven insights. Widely-used dataset search systems rely…
Magneto: Combining Small and Large Language Models for Schema Matching
Yurong Liu, Eduardo Pena, Aecio Santos +2
Recent advances in language models opened new opportunities to address complex schema matching tasks. Schema matching approaches have been proposed that demonstrate the usefulness…
Kernel Banzhaf: A Fast and Robust Estimator for Banzhaf Values
Yurong Liu, R. Teal Witter, Flip Korn +4
Banzhaf values provide a popular, interpretable alternative to the widely-used Shapley values for quantifying the importance of features in machine learning models. Like Shapley va…
ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models
Benjamin Feuer, Yurong Liu, Chinmay Hegde +1
Existing deep-learning approaches to semantic column type annotation (CTA) have important shortcomings: they rely on semantic types which are fixed at training time; require a larg…
A Fine-Grained Analysis of Public Opinion toward Chinese Technology Companies on Reddit
Enting Zhou, Yurong Liu, Hanjia Lyu +1
In the face of the growing global influence and prevalence of Chinese technology companies, governments worldwide have expressed concern and mistrust toward these companies. There…