AirGroundBench is a new diagnostic benchmark exposing that MLLMs handle basic spatial perception but struggle with cross-view alignment, transformation reasoning, and embodied navigation under heterogeneous air-ground views.
Vln-mme: Diagnosing mllms as language-guided visual navigation agents.arXiv preprint arXiv:2512.24851, 2025
3 Pith papers cite this work. Polarity classification is still indexing.
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Qwen-RobotNav provides a parameterized navigation model trained on 15.6M samples with vision-language co-training that achieves SOTA results on benchmarks and zero-shot transfer to real robots.
Proposes cost-aware question selection for ambiguous object navigation via information-gain analysis on corpora, a cost-penalizing benchmark, and a zero-shot MLLM agent.
citing papers explorer
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AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration
AirGroundBench is a new diagnostic benchmark exposing that MLLMs handle basic spatial perception but struggle with cross-view alignment, transformation reasoning, and embodied navigation under heterogeneous air-ground views.
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Ask When It Pays: Cost-Aware Open-Ended Interaction for Instance Goal Navigation
Proposes cost-aware question selection for ambiguous object navigation via information-gain analysis on corpora, a cost-penalizing benchmark, and a zero-shot MLLM agent.