Search Results for author:
Found 7 papers, 2 papers with code
SEED: Domain-Specific Data Curation With Large Language Models
SEED uses these generated modules to process most of the data records and dynamically decides when the LLM should step in to directly process some individual records, possibly using the data-access modules to retrieve relevant information from the data sources to assist the LLM in solving the task.
TagMe: GPS-Assisted Automatic Object Annotation in Videos
We show TagMe can produce high-quality object annotations in a fully-automatic and low-cost way.
Technical Report on Data Integration and Preparation
In this report, we highlight a number of tools that can be used to simplify data integration and preparation steps.
Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data
Large, human-annotated datasets are central to the development of natural language processing models.
Duoquest: A Dual-Specification System for Expressive SQL Queries
We present results from user studies in which Duoquest demonstrates a 62. 5% absolute increase in query construction accuracy over a state-of-the-art NLI and comparable accuracy to a PBE system on a more limited workload supported by the PBE system.
Databases
Physical Representation-based Predicate Optimization for a Visual Analytics Database
Modern extraction techniques are based on deep convolutional neural networks (CNNs) and can classify objects within images with astounding accuracy.
Database Learning: Toward a Database that Becomes Smarter Every Time
Also, processing more queries should continuously enhance our knowledge of the underlying distribution, and hence lead to increasingly faster response times for future queries.
