4 citations · 12 across the 15 of their papers we have counts for
7 papers · 1 filter
Affective Color Scales for Colormap Data Visualizations
Halle C. Braun, Kushin Mukherjee, Seth R. Gorelik +1
Research on affective visualization design has shown that color is an especially powerful feature for influencing the emotional connotation of visualizations. Associations between…
Presenting Large Language Models as Companions Affects What Mental Capacities People Attribute to Them
Allison Chen, Sunnie S. Y. Kim, Angel Franyutti +4
How might messages about large language models (LLMs) found in public discourse influence the way people think about and interact with these models? To explore this question, we ra…
Uncovering the Computational Ingredients of Human-Like Representations in LLMs
Zach Studdiford, Timothy T. Rogers, Kushin Mukherjee +1
The human ability to translate diverse perceptual and linguistic inputs into structured behavior has been thought to rest on learning robust representations of concepts. The rapid…
EncQA: Benchmarking Vision-Language Models on Visual Encodings for Charts
Kushin Mukherjee, Donghao Ren, Dominik Moritz +1
Multimodal vision-language models (VLMs) continue to achieve ever-improving scores on chart understanding benchmarks. Yet, we find that this progress does not fully capture the bre…
Human-centered evaluation of data visualization understanding in vision-language models
Arnav Verma, Kushin Mukherjee, Christopher Potts +2
Data visualization understanding, which requires integrating visual, numerical, and linguistic inputs, poses fundamental challenges to multimodal reasoning. Recently developed visi…
AI-enhanced semantic feature norms for 786 concepts
Siddharth Suresh, Kushin Mukherjee, Tyler Giallanza +4
Semantic feature norms have been foundational in the study of human conceptual knowledge, yet traditional methods face trade-offs between concept/feature coverage and verifiability…
Evaluating Steering Techniques using Human Similarity Judgments
Zach Studdiford, Timothy T. Rogers, Siddharth Suresh +1
Current evaluations of Large Language Model (LLM) steering techniques focus on task-specific performance, overlooking how well steered representations align with human cognition. U…