PhysCodeBench benchmark and SMRF multi-agent framework enable better AI generation of physically accurate 3D simulation code, boosting performance by 31 points over baselines.
In: 2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
3 Pith papers cite this work. Polarity classification is still indexing.
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A scoping review and personal reflections identify robot wrangling as a complex umbrella term and generate design implications for supporting wranglers as individuals and within broader service ecologies.
Embodied AI requires treating privacy as a lifecycle architectural constraint rather than a stage-local feature, addressed via the proposed SPINE framework with a multi-criterion privacy classification matrix.
citing papers explorer
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PhysCodeBench: Benchmarking Physics-Aware Symbolic Simulation of 3D Scenes via Self-Corrective Multi-Agent Refinement
PhysCodeBench benchmark and SMRF multi-agent framework enable better AI generation of physically accurate 3D simulation code, boosting performance by 31 points over baselines.
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Designing for Robot Wranglers: A Synthesis of Literature and Practice
A scoping review and personal reflections identify robot wrangling as a complex umbrella term and generate design implications for supporting wranglers as individuals and within broader service ecologies.
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Position: Embodied AI Requires a Privacy-Utility Trade-off
Embodied AI requires treating privacy as a lifecycle architectural constraint rather than a stage-local feature, addressed via the proposed SPINE framework with a multi-criterion privacy classification matrix.