79 citations · 325 across the 44 of their papers we have counts for
49 papers
NOMADD: Numerical Optimization of Models Adapting to Data Drift
Swapn Shah, Keith Burghardt
Tabular model performance degrades when feature distributions change over time or the relationship between features and outcome variables change over time, known as data drift and…
FAMOSE: A ReAct Approach to Automated Feature Discovery
Keith Burghardt, Jienan Liu, Sadman Sakib +2
Feature engineering remains a critical yet challenging bottleneck in machine learning, particularly for tabular data, as identifying optimal features from an exponentially large fe…
CHRONEX-US: City-level historical road network expansion dataset for the conterminous United States
Johannes H. Uhl, Keith A. Burghardt, Stefan Leyk
Geospatial datasets on the long-term evolution of road networks are scarce, hampering our quantitative understanding of how the contemporary road network has evolved over the cours…
Large Language Models Reveal Information Operation Goals, Tactics, and Narrative Frames
Keith Burghardt, Kai Chen, Kristina Lerman
Adversarial information operations can destabilize societies by undermining fair elections, manipulating public opinions on policies, and promoting scams. Despite their widespread…
SoMeR: Multi-View User Representation Learning for Social Media
Siyi Guo, Keith Burghardt, Valeria Pantè +1
Social media user representation learning aims to capture user preferences, interests, and behaviors in low-dimensional vector representations. These representations are critical t…
GET-Tok: A GenAI-Enriched Multimodal TikTok Dataset Documenting the 2022 Attempted Coup in Peru
Gabriela Pinto, Keith Burghardt, Kristina Lerman +1
TikTok is one of the largest and fastest-growing social media sites in the world. TikTok features, however, such as voice transcripts, are often missing and other important feature…