most citedBeyond Quantification: Navigating Uncertainty in Professional AI Systems

6 citations · 9 across the 12 of their papers we have counts for

collaborators

15 papers

cs.HC2025

A Design Space for Intelligent Agents in Mixed-Initiative Visual Analytics

Tobias Stähle, Matthijs Jansen op de Haar, Sophia Boyer +3

Mixed-initiative visual analytics (VA) systems, where human and artificial intelligence (AI) agents collaborate as equal partners during analysis, represented a paradigm shift in h…

cs.HC2025

SemanticTours: A Conceptual Framework for Non-Linear, Knowledge Graph-Driven Data Tours

Daniel Fürst, Matthijs Jansen op de Haar, Mennatallah El-Assady +2

Interactive tours help users explore datasets and provide onboarding. They rely on a linear sequence of views, showing a curated set of relevant data selections and introduce user…

cs.HC2025

Dia-Lingle: A Gamified Interface for Dialectal Data Collection

Jiugeng Sun, Rita Sevastjanova, Sina Ahmadi +2

Dialects suffer from the scarcity of computational textual resources as they exist predominantly in spoken rather than written form and exhibit remarkable geographical diversity. C…

cs.HC2025

CafGa: Customizing Feature Attributions to Explain Language Models

Alan Boyle, Furui Cheng, Vilém Zouhar +1

Feature attribution methods, such as SHAP and LIME, explain machine learning model predictions by quantifying the influence of each input component. When applying feature attributi…

cs.HC20256 cited

Beyond Quantification: Navigating Uncertainty in Professional AI Systems

Sylvie Delacroix, Diana Robinson, Umang Bhatt +12

The growing integration of large language models across professional domains transforms how experts make critical decisions in healthcare, education, and law. While significant res…

cs.HC20251 cited

DxHF: Providing High-Quality Human Feedback for LLM Alignment via Interactive Decomposition

Danqing Shi, Furui Cheng, Tino Weinkauf +2

Human preferences are widely used to align large language models (LLMs) through methods such as reinforcement learning from human feedback (RLHF). However, the current user interfa…