RAO-Nav: Probing Omni-Language Models for Zero-shot Semantic Audio-Visual Navigation
cs.AI
Submitted: 2026-09-26
Updated: 2026-09-26
Code: https://github.com/rikeilong/OmniAV_Nav
Terminology
Sources
- Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
- $A^2$Nav: Action-Aware Zero-Shot Robot Navigation by Exploiting Vision-and-Language Ability of Foundation Models
- Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigation
- NavBench: Probing Multimodal Large Language Models for Embodied Navigation
- OctoNav: Towards Generalist Embodied Navigation
- Matterport3D: Learning from RGB-D Data in Indoor Environments
- Qwen3-VL Technical Report
- Visual Instruction Tuning
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
- VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection