Uni-RS: A Spatially Faithful Unified Understanding and Generation Model for Remote Sensing
cs.CV, cs.AI
Submitted: 2026-01-25
Updated: 2026-10-13
Terminology
Sources
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset
- Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
- Emerging Properties in Unified Multimodal Pretraining
- GeoVLM-R1: Reinforcement Fine-Tuning for Improved Remote Sensing Reasoning
- SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model
- GeoReason: Aligning Thinking And Answering In Remote Sensing Vision-Language Models Via Logical Consistency Reinforcement Learning
- Towards Faithful Reasoning in Remote Sensing: A Perceptually-Grounded GeoSpatial Chain-of-Thought for Vision-Language Models
- SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding
- Transfer between Modalities with MetaQueries
- Chameleon: Mixed-Modal Early-Fusion Foundation Models
- Emu3: Next-Token Prediction is All You Need
- GeoZero: Incentivizing Reasoning from Scratch on Geospatial Scenes
- Qwen-Image Technical Report
- SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers
- Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities
- Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
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