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• GeoPRM has remarkable cross-model generalization capabilities.result 80%
• GeoSolver achieves state-of-the-art performance across diverse remote sensing benchmarks.result 90%
• GeoPRM enables robust Test-Time Scaling (TTS) that enhances both GeoSolver-9B and general-purpose VLMs.technical 85%
• Geo-PRM-2M is a large-scale, token-level process supervision dataset synthesized via entropy-guided Monte Carlo Tree Search (MCTS) and targeted visual hallucination injection.method 90%
• Process-Aware Tree-GRPO integrates tree-structured exploration with a faithfulness-weighted reward mechanism to assign credit to intermediate steps.method 85%
• Ensuring visual faithfulness of intermediate reasoning steps is a critical bottleneck in remote sensing VLMs.limitation 75%
• GeoSolver transitions remote sensing reasoning toward verifiable, process-supervised reinforcement learning.method 85%
• GeoPRM is a token-level process reward model that provides granular faithfulness feedback.technical 90%

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