221 citations · 276 across the 13 of their papers we have counts for
13 papers
BenchPress: A Human-in-the-Loop Annotation System for Rapid Text-to-SQL Benchmark Curation
Fabian Wenz, Omar Bouattour, Devin Yang +4
Large language models (LLMs) have been successfully applied to many tasks, including text-to-SQL generation. However, much of this work has focused on publicly available datasets,…
Mind the Data Gap: Bridging LLMs to Enterprise Data Integration
Moe Kayali, Fabian Wenz, Nesime Tatbul +1
Leading large language models (LLMs) are trained on public data. However, most of the world's data is dark data that is not publicly accessible, mainly in the form of private organ…
BEAVER: An Enterprise Benchmark for Text-to-SQL
Peter Baile Chen, Devin Yang, Weiyue Li +6
Existing text-to-SQL benchmarks have largely been constructed from public databases with well-structured schemas and simplistic question-SQL pairs. While large language models (LLM…
Making LLMs Work for Enterprise Data Tasks
Çağatay Demiralp, Fabian Wenz, Peter Baile Chen +3
Large language models (LLMs) know little about enterprise database tables in the private data ecosystem, which substantially differ from web text in structure and content. As LLMs'…
CascadeServe: Unlocking Model Cascades for Inference Serving
Ferdi Kossmann, Ziniu Wu, Alex Turk +3
Machine learning (ML) models are increasingly deployed to production, calling for efficient inference serving systems. Efficient inference serving is complicated by two challenges:…
Kairos: Efficient Temporal Graph Analytics on a Single Machine
Joana M. F. da Trindade, Julian Shun, Samuel Madden +1
Many important societal problems are naturally modeled as algorithms over temporal graphs. To date, however, most graph processing systems remain inefficient as they rely on distri…
Event Detection on Twitter
Ozlem Ceren Sahin, Nesime Tatbul, Pinar Karagoz
Detecting events by using social media has been an active research problem. In this work, we investigate and compare the performance of two methods for event detection in Twitter b…
Extract-Transform-Load for Video Streams
Ferdinand Kossmann, Ziniu Wu, Eugenie Lai +4
Social media, self-driving cars, and traffic cameras produce video streams at large scales and cheap cost. However, storing and querying video at such scales is prohibitively expen…
Flow-Loss: Learning Cardinality Estimates That Matter
Parimarjan Negi, Ryan Marcus, Andreas Kipf +4
Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make…
A Skew-Sensitive Evaluation Framework for Imbalanced Data Classification
Min Du, Nesime Tatbul, Brian Rivers +7
Class distribution skews in imbalanced datasets may lead to models with prediction bias towards majority classes, making fair assessment of classifiers a challenging task. Metrics…
Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series
Vincent Jacob, Fei Song, Arnaud Stiegler +3
Access to high-quality data repositories and benchmarks have been instrumental in advancing the state of the art in many experimental research domains. While advanced analytics tas…
MISIM: A Neural Code Semantics Similarity System Using the Context-Aware Semantics Structure
Fangke Ye, Shengtian Zhou, Anand Venkat +10
Code semantics similarity can be used for many tasks such as code recommendation, automated software defect correction, and clone detection. Yet, the accuracy of such systems has n…
Bao: Learning to Steer Query Optimizers
Ryan Marcus, Parimarjan Negi, Hongzi Mao +3
Query optimization remains one of the most challenging problems in data management systems. Recent efforts to apply machine learning techniques to query optimization challenges hav…