SenseBench is the first physics-based benchmark with 10K+ instances and dual protocols to evaluate VLMs on remote sensing low-level perception and diagnostic description, revealing domain bias and specific failure modes.
Mixed citations
Falcon: A remote sensing vision-language foundation model
Mixed citation behavior. Most common role is background (40%).
8
Pith papers citing it
Background
40% of classified citations
citation-role summary
background 2
baseline 2
method 1
citation-polarity summary
years
2026 8verdicts
UNVERDICTED 8representative citing papers
Unfine-tuned MLLMs outperform fine-tuned models on remote sensing image captioning when captions are scored by their ability to reconstruct the source image, and a training-free self-correction method achieves SOTA performance.
RemoteAgent uses RL fine-tuning on VagueEO to align MLLMs for vague EO intent recognition, handling simple tasks internally and routing dense predictions to tools via Model Context Protocol.
Agentic AI faces structural challenges in remote sensing due to geospatial data properties and workflow constraints, requiring EO-native agents built around structured state, tool-aware reasoning, and validity-aware evaluation.
RemoteShield improves robustness of Earth observation MLLMs by training on semantic equivalence clusters of clean and perturbed inputs via preference learning to maintain consistent reasoning under noise.
DiffuSAM fuses diffusion-based localization cues with SAM models to deliver over 14% higher Acc@0.5 in zero-shot object grounding for remote sensing imagery compared to prior methods.
A text-guided framework for remote sensing image transmission uses low-res images and compact text to reduce data volume to 2%, with text-conditioned reconstruction achieving PSNRs of 16.36-27.41 dB on tested datasets.
A survey of UAV vision-and-language navigation that establishes a methodological taxonomy, reviews resources and challenges, and proposes a forward-looking research roadmap.
citing papers explorer
-
Vision-and-Language Navigation for UAVs: Progress, Challenges, and a Research Roadmap
A survey of UAV vision-and-language navigation that establishes a methodological taxonomy, reviews resources and challenges, and proposes a forward-looking research roadmap.