SBAC uses sketching and multimodal LLMs to help users refine underspecified access control preferences into complete, validated policies through iterative human-AI collaboration.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
fields
cs.HC 3roles
background 2polarities
background 2representative citing papers
Evalet applies functional fragmentation to deliver fragment-level qualitative analysis of LLM evaluations, with a user study showing 48% more misalignment detections than holistic scoring.
AI systems risk reducing the perceived authenticity of prayer when they take too much guiding agency, so designs should preserve user agency through interpretive openness or allow non-use.
citing papers explorer
-
Sketch-based Access Control: A Multimodal Interface for Translating User Preferences into Intent-Aligned Policies
SBAC uses sketching and multimodal LLMs to help users refine underspecified access control preferences into complete, validated policies through iterative human-AI collaboration.
-
Evalet: Evaluating Large Language Models through Functional Fragmentation
Evalet applies functional fragmentation to deliver fragment-level qualitative analysis of LLM evaluations, with a user study showing 48% more misalignment detections than holistic scoring.
-
Value-Sensitive AI for Prayer: Balancing the Agencies Between Human and AI Agents in Spiritual Context
AI systems risk reducing the perceived authenticity of prayer when they take too much guiding agency, so designs should preserve user agency through interpretive openness or allow non-use.