152 citations
- Carnegie Mellon UniversityUS5 papers
- Ludwig-Maximilians-Universität MünchenDE5 papers
- Center for Strategic ResearchRU4 papers
- Robotic Research (United States)US4 papers
- LMU KlinikumDE3 papers
- Optim Design (United States)US3 papers
- Aalborg UniversityDK2 papers
- Centre for Arctic Gas Hydrate, Environment and ClimateNO2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Columbia UniversityUS2 papers
- Stanford UniversityUS2 papers
- UiT The Arctic University of NorwayNO2 papers
7 papers · 1 filter
Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models
Georg Ahnert, Anna-Carolina Haensch, Barbara Plank +1
Many in-silico simulations of human survey responses with large language models (LLMs) focus on generating closed-ended survey responses, whereas LLMs are typically trained to gene…
Two warm Earth-sized exoplanets and an Earth-sized candidate in the M5V-M6V binary system TOI-2267
S. Zúñiga-Fernández, F. J. Pozuelos, M. Dévora-Pajares +63
We report two warm Earth-sized exoplanets orbiting the close binary TOI-2267 (M5+M6, separation ~8 au). Data from TESS and ground-based facilities confirm the planets, but we canno…
EmbedOR: Provable Cluster-Preserving Visualizations with Curvature-Based Stochastic Neighbor Embeddings
Tristan Luca Saidi, Abigail Hickok, Bastian Rieck +1
Stochastic Neighbor Embedding (SNE) algorithms like UMAP and tSNE often produce visualizations that do not preserve the geometry of noisy and high dimensional data. In particular,…
SHAining on Process Mining: Explaining Event Log Characteristics Impact on Algorithms
Andrea Maldonado, Christian M. M. Frey, Sai Anirudh Aryasomayajula +3
Process mining aims to extract and analyze insights from event logs, yet algorithm metric results vary widely depending on structural event log characteristics. Existing work often…
Machine Understanding of Scientific Language
Dustin Wright
Scientific information expresses human understanding of nature. This knowledge is largely disseminated in different forms of text, including scientific papers, news articles, and d…
Sparser, Better, Faster, Stronger: Sparsity Detection for Efficient Automatic Differentiation
Adrian Hill, Guillaume Dalle
From implicit differentiation to probabilistic modeling, Jacobian and Hessian matrices have many potential use cases in Machine Learning (ML), but they are viewed as computationall…