MGRL-RSCC: Multi-Granularity Reward Reinforcement Learning for Fine-Grained Remote Sensing Change Captioning

arXiv:2609.26166 · cs.CV, cs.AI, cs.LG · Submitted 2026-08-09 · Read on arXiv

cs.CV, cs.AI, cs.LG

Submitted: 2026-08-09

Updated: 2026-08-09

Code: https://github.com/Event-AHU/MGRL-RSCC

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 35× in this paper · explained in 4 episodes
• Transformer — 16× in this paper · explained in 2 episodes
• Remote Sensing Change Captioning — 15× in this paper
• Consistency — 10× in this paper · explained in 3 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Exposure Bias — 8× in this paper · explained in 2 episodes
• Reward Function — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Ablation study — 4× in this paper · explained in 1 episode
• Actor — 4× in this paper · explained in 3 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Robustness — 3× in this paper · explained in 5 episodes
• Core — 2× in this paper · explained in 2 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptive Graph — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Convolutional Neural Network — 1× in this paper
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Dynamic Weighting — 1× in this paper · explained in 3 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Structured Reasoning — 1× in this paper · explained in 3 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Two-Stage Optimization — 1× in this paper · explained in 2 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes

Sources

• Actor-Critic Sequence Training for Image Captioning
• CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
• DFM: Difference Feature Modeling with Text-Guided Gated Contrastive Loss for Remote Sensing Image Change Captioning
• UAV as Urban Construction Change Monitor: A New Benchmark and Change Captioning Model

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