ReVA: A Scene-Centric Dataset Beyond Repetition for Remote Sensing Video Question Answering

arXiv:2609.35507 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/zyaocoder/ReVA

Terminology

• Benchmark — 24× in this paper · explained in 2 episodes
• Alignment — 17× in this paper · explained in 1 episode
• Grounding — 16× in this paper · explained in 3 episodes
• Causal Reasoning — 12× in this paper · explained in 2 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Verification — 10× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Multimodal Reasoning — 4× in this paper · explained in 5 episodes
• Temporal Reasoning — 4× in this paper · explained in 2 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• AdamW Optimizer — 2× in this paper · explained in 1 episode
• Hallucination — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Systematic Bias — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Lexical Diversity — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• UAV with the Federal Aviation Administration — 1× in this paper
• alpha — 1× in this paper · explained in 1 episode

Sources

• GPT-4 Technical Report
• Qwen Technical Report
• Qwen3-VL Technical Report
• VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• LLaVA-OneVision: Easy Visual Task Transfer
• VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling
• Decoupled Weight Decay Regularization
• Reasoning with Pixel-level Precision: QVLM Architecture and SQuID Dataset for Quantitative Geospatial Analytics
• Memory-Augmented Multimodal Large Language Models for Small Object Understanding in Streaming Aerial Videos
• STAR: A Benchmark for Situated Reasoning in Real-World Videos
• RemoteReasoner: Towards Unifying Geospatial Reasoning Workflow
• Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding
• Thinking With Videos: Multimodal Tool-Augmented Reinforcement Learning for Long Video Reasoning
• LLaVA-Video: Video Instruction Tuning With Synthetic Data
• RSVideo: Are Your Vision-Language Models Ready for Remote Sensing Videos?
• InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models