activity
20192022
most citedAsk Me Anything: A simple strategy for prompting language models

75 citations · 78 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2021

Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text

Maya Varma, Laurel Orr, Sen Wu +3

Named entity disambiguation (NED), which involves mapping textual mentions to structured entities, is particularly challenging in the medical domain due to the presence of rare ent…

cs.LG20212 cited

Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems

Laurel Orr, Atindriyo Sanyal, Xiao Ling +2

The industrial machine learning pipeline requires iterating on model features, training and deploying models, and monitoring deployed models at scale. Feature stores were developed…

cs.CL2020

Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation

Laurel Orr, Megan Leszczynski, Simran Arora +4

A challenge for named entity disambiguation (NED), the task of mapping textual mentions to entities in a knowledge base, is how to disambiguate entities that appear rarely in the t…

cs.DB2020

Sample Debiasing in the Themis Open World Database System (Extended Version)

Laurel Orr, Magda Balazinska, Dan Suciu

Open world database management systems assume tuples not in the database still exist and are becoming an increasingly important area of research. We present Themis, the first open…

cs.DB20201 cited

Mosaic: A Sample-Based Database System for Open World Query Processing

Laurel Orr, Samuel Ainsworth, Walter Cai +3

Data scientists have relied on samples to analyze populations of interest for decades. Recently, with the increase in the number of public data repositories, sample data has become…

cs.DB2019

EntropyDB: A Probabilistic Approach to Approximate Query Processing

Laurel Orr, Magdalena Balazinska, Dan Suciu

We present EntropyDB, an interactive data exploration system that uses a probabilistic approach to generate a small, query-able summary of a dataset. Departing from traditional sum…