Publications (20)
Self-Supervised Multi-Object Tracking with Cross-Input Consistency
Favyen Bastani, Songtao He, Sam Madden
In this paper, we propose a self-supervised learning procedure for training a robust multi-object tracking (MOT) model given only unlabeled video. While several self-supervisory le…
TagMe: GPS-Assisted Automatic Object Annotation in Videos
Songtao He, Favyen Bastani, Mohammad Alizadeh +4
Training high-accuracy object detection models requires large and diverse annotated datasets. However, creating these data-sets is time-consuming and expensive since it relies on h…
Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generation
Zihui Gu, Ju Fan, Nan Tang +7
Zero-shot NL2SQL is crucial in achieving natural language to SQL that is adaptive to new environments (e.g., new databases, new linguistic phenomena or SQL structures) with zero an…
Updating Street Maps using Changes Detected in Satellite Imagery
Favyen Bastani, Songtao He, Satvat Jagwani +5
Accurately maintaining digital street maps is labor-intensive. To address this challenge, much work has studied automatically processing geospatial data sources such as GPS traject…
TabulaROSA: Tabular Operating System Architecture for Massively Parallel Heterogeneous Compute Engines
Jeremy Kepner, Ron Brightwell, Alan Edelman +10
The rise in computing hardware choices is driving a reevaluation of operating systems. The traditional role of an operating system controlling the execution of its own hardware is…
SEED: Domain-Specific Data Curation With Large Language Models
Zui Chen, Lei Cao, Sam Madden +7
Data curation tasks that prepare data for analytics are critical for turning data into actionable insights. However, due to the diverse requirements of applications in different do…
RoadTracer: Automatic Extraction of Road Networks from Aerial Images
Favyen Bastani, Songtao He, Sofiane Abbar +5
Mapping road networks is currently both expensive and labor-intensive. High-resolution aerial imagery provides a promising avenue to automatically infer a road network. Prior work…
The Case for RodentStore, an Adaptive, Declarative Storage System
Philippe Cudre-Mauroux, Eugene Wu, Sam Madden
Recent excitement in the database community surrounding new applications?analytic, scientific, graph, geospatial, etc.?has led to an explosion in research on database storage syste…
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling
Oscar Moll, Favyen Bastani, Sam Madden +3
Capturing and processing video is increasingly common as cameras become cheaper to deploy. At the same time, rich video understanding methods have progressed greatly in the last de…
Machine-Assisted Map Editing
Favyen Bastani, Songtao He, Sofiane Abbar +4
Mapping road networks today is labor-intensive. As a result, road maps have poor coverage outside urban centers in many countries. Systems to automatically infer road network graph…
MultiScope: Efficient Video Pre-processing for Exploratory Video Analytics
Favyen Bastani, Sam Madden
Performing analytics tasks over large-scale video datasets is increasingly common in a wide range of applications. These tasks generally involve object detection and tracking opera…
SkyQuery: An Aerial Drone Video Sensing Platform
Favyen Bastani, Songtao He, Ziwen Jiang +2
Video-based sensing from aerial drones, especially small multirotor drones, can provide rich data for numerous applications, including traffic analysis (computing traffic flow volu…
Attendee-Sourcing: Exploring The Design Space of Community-Informed Conference Scheduling
Anant Bhardwaj, Juho Kim, Steven Dow +4
Constructing a good conference schedule for a large multi-track conference needs to take into account the preferences and constraints of organizers, authors, and attendees. Creatin…
Beyond Road Extraction: A Dataset for Map Update using Aerial Images
Favyen Bastani, Sam Madden
The increasing availability of satellite and aerial imagery has sparked substantial interest in automatically updating street maps by processing aerial images. Until now, the commu…
Lingua Manga: A Generic Large Language Model Centric System for Data Curation
Zui Chen, Lei Cao, Sam Madden
Data curation is a wide-ranging area which contains many critical but time-consuming data processing tasks. However, the diversity of such tasks makes it challenging to develop a g…
RoTaR: Efficient Row-Based Table Representation Learning via Teacher-Student Training
Zui Chen, Lei Cao, Sam Madden
We propose RoTaR, a row-based table representation learning method, to address the efficiency and scalability issues faced by existing table representation learning methods. The ke…
Rapid Sampling for Visualizations with Ordering Guarantees
Albert Kim, Eric Blais, Aditya Parameswaran +3
Visualizations are frequently used as a means to understand trends and gather insights from datasets, but often take a long time to generate. In this paper, we focus on the problem…
Optimizing Query Predicates with Disjunctions for Column-Oriented Engines
Albert Kim, Atalay Mert Ileri, Sam Madden
Database research has always given limited attention to optimizing predicates with disjunctions. What little past work there is, has mostly focused on optimizations for traditional…
Inferring and Improving Street Maps with Data-Driven Automation
Favyen Bastani, Songtao He, Satvat Jagwani +7
Street maps are a crucial data source that help to inform a wide range of decisions, from navigating a city to disaster relief and urban planning. However, in many parts of the wor…
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
Nan Tang, Ju Fan, Fangyi Li +5
Can AI help automate human-easy but computer-hard data preparation tasks that burden data scientists, practitioners, and crowd workers? We answer this question by presenting RPT, a…