14 citations · 41 across the 13 of their papers we have counts for
4 papers · 1 filter
What People Almost Did: Evaluating LLM Social Simulations Beyond Behavioral Fit
JaeWon Kim, Angie Boggust
LLM-based social simulations are primarily evaluated for behavioral fit, testing whether agents reproduce the actions or response distributions of the people they are simulating. H…
Creo: From One-Shot Image Generation to Progressive, Co-Creative Ideation
Zoe De Simone, Angie Boggust, Fredo Durand +2
Text-to-image (T2I) systems enable rapid generation of high-fidelity imagery but are misaligned with how visual ideas develop. T2I systems generate outputs that make implicit visua…
Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments
Angie Boggust, Venkatesh Sivaraman, Yannick Assogba +3
To deploy machine learning models on-device, practitioners use compression algorithms to shrink and speed up models while maintaining their high-quality output. A critical aspect o…
Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples
Angie Boggust, Brandon Carter, Arvind Satyanarayan
Embeddings mapping high-dimensional discrete input to lower-dimensional continuous vector spaces have been widely adopted in machine learning applications as a way to capture domai…