XR Blocks supplies an LLM-optimized Reality Model and Vibe Coding XR workflow that converts high-level prompts into working physics-aware XR applications with high one-shot success.
Karger, and David D
4 Pith papers cite this work, alongside 9 external citations. Polarity classification is still indexing.
4
Pith papers citing it
9
external citations · external index
citation-role summary
background 1
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
A generative-AI pipeline dynamically generates and anchors virtual assets to match the shape of physical props, enabling adaptive passive haptics in MR that users rate higher in realism, immersion, and enjoyment than static baselines.
Intent Lenses infer capture-time user intent from photos via LLMs to create dynamic, reusable interactive objects that generate and organize structured visual notes for later sensemaking.
Committing to explicit meaning via a domain-grounded vocabulary of individuals, actions, facts, and concepts improves software usability, enables modular LLM code generation, and supports accountable agent behavior.
citing papers explorer
-
Vibe Coding XR: Accelerating AI + XR Prototyping with XR Blocks and Gemini
XR Blocks supplies an LLM-optimized Reality Model and Vibe Coding XR workflow that converts high-level prompts into working physics-aware XR applications with high one-shot success.
-
Prop-Chromeleon: Adaptive Haptic Props in Mixed Reality through Generative Artificial Intelligence
A generative-AI pipeline dynamically generates and anchors virtual assets to match the shape of physical props, enabling adaptive passive haptics in MR that users rate higher in realism, immersion, and enjoyment than static baselines.
-
Intent Lenses: Inferring Capture-Time Intent to Transform Opportunistic Photo Captures into Structured Visual Notes
Intent Lenses infer capture-time user intent from photos via LLMs to create dynamic, reusable interactive objects that generate and organize structured visual notes for later sensemaking.
-
Making Software Meaningful
Committing to explicit meaning via a domain-grounded vocabulary of individuals, actions, facts, and concepts improves software usability, enables modular LLM code generation, and supports accountable agent behavior.