Remote sensing visual question answering (RS-VQA) requires answers that truly depend on image evidence, yet current remote sensing multimodal large language models (RS MLLMs) are still evaluated mainly by accuracy, which cannot reveal whether a correct answer was produced without using the image. This setting introduces three challenges: demonstrations retrieved across different ground sample distances (GSD), sensors, and city textures may be poorly matched; real queries often involve long visual contexts from multi-scale tiles, multi-temporal frames, and retrieved knowledge, where evidence can be diluted and errors can propagate through multi-step reasoning; and prior-only answering remains invisible to standard metrics. We present AVA, a training-free framework that wraps a frozen RS MLLM with three modules. GDR performs GSD-bucketed, scene-graph-based demonstration retrieval and filters demonstrations whose answers are unsupported by their images. MACE decomposes each query into an evidence-typed sub-question DAG, routes sub-questions to suitable perception tools, and records verified provenance in a shared evidence ledger with bounded re-perception. CVA audits the final answer through counterfactual perturbations of cited evidence, including ablation and swap, and computes a visual-dependency score for confidence calibration and evidence-forcing re-query. On RSVQA-LR/HR, VRSBench, and LHRS-Bench, AVA improves average accuracy by up to 2.40 points over the strongest same-setting baselines, raises the visual-dependency score from 0.28 to 0.49, reduces the prior-only answer rate from 46.2 percent to 21.7 percent, and lowers the hallucination rate from 17.1 percent to 9.8 percent, with 2.6x the cost of a single backbone forward pass and no fine-tuning.
GeoEyes: On-Demand Visual Focusing for Evidence-Grounded Understanding of Ultra-High-Resolution Remote Sensing Imagery
National University of Defense Technology, China（国防科技大学）；Beijing University of Posts and Telecommunications, China（北京邮电大学）；University of the Chinese Academy of Sciences, China（中国科学院大学）；Shanghai Jiao Tong University, China（上海交通大学）；Wuhan University, China（武汉大学）；Chinese Academy of Science, China（中国科学院）；Tsinghua University, China（清华大学）；Renmin University of China, China（中国人民大学）
GeoChat: Grounded Large Vision-Language Model for Remote Sensing
Mohamed bin Zayed University of AI（穆罕默德·本·扎耶德人工智能大学）；Birla Institute of Technology & Science, Hyderabad（海得拉巴贝拉理工学院）；Australian National University（澳大利亚国立大学）；Linköping University（林雪平大学）
Remote Sensing Retrieval-Augmented Generation: Bridging Remote Sensing Imagery and Comprehensive Knowledge with a Multi-Modal Dataset and Retrieval-Augmented Generation Model
School of Cyber Science and Technology, University of Science and Technology of China（信息科学技术学院，中国科学技术大学）；China Academy of Electronics and Information Technology（电子信息技术研究院）
LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation
School of Computer Science, China University of Geosciences（中国地质大学（北京）计算机学院）；PRADA Lab, King Abdullah University of Science and Technology（科廷大学PRADA实验室）；Department of Computer Science, University of Exeter（埃克塞特大学计算机科学系）
GeoMeld: Toward Semantically Grounded Foundation Models for Remote Sensing
Indian Institute of Technology Bombay（印度理工学院孟买分校）；Space Applications Centre, ISRO（印度空间研究组织空间应用中心）；University of Trento（特伦托大学）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
Asking like Socrates: Socrates helps VLMs understand remote sensing images
School of Geosciences and Info-Physics, Central South University（中南大学地球科学与信息物理学院）；Baidu Inc.（百度公司）；School of Earth Sciences, Zhejiang University（浙江大学地球科学学院）
PHASE-Net: Physics-Grounded Harmonic Attention System for Efficient Remote Photoplethysmography Measurement
Great Bay University（大湾大学）；Hefei University of Technology（合肥工业大学）；Macao Polytechnic University（澳门 polytechnic 大学）；University of Science and Technology Beijing（北京科技大学）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学深圳分校）；Dongguan Key Laboratory for Intelligence and Information Technology（东莞智能与信息科技重点实验室）
GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing
Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Australian National University（澳大利亚国立大学）；The University of Western Australia（西澳大利亚大学）
AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutation
Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China（南方科技大学计算机科学与工程系，深圳，中国）；School of EEE, Nanyang Technological University (NTU), Singapore（南洋理工大学电子工程学院，新加坡）；CFAR, Agency for Science, Technology and Research (A*STAR), Singapore（科技研究局（A*STAR）的CFAR，新加坡）
Disentangling Hardness from Noise: An Uncertainty-Driven Model-Agnostic Framework for Long-Tailed Remote Sensing Classification
Research Center for Space Computing System, Zhejiang Lab（空间计算系统研究中心，浙江实验室）；School of Cyber Science and Engineering, Zhengzhou University（网络安全工程学院，郑州大学）；School of Computer Science and Technology, Xi'an Jiaotong University（计算机科学与技术学院，西安交通大学）
BigEarthNet.txt: A Large-Scale Multi-Sensor Image-Text Dataset and Benchmark for Earth Observation
BIFOLD（柏林智能数据与机器学习研究所）；Technische Universität Berlin（柏林工业大学）；University of Trento（特伦托大学）；National Technical University（雅典国家技术大学）；National Observatory of Athens（雅典国家天文台）
Adaptive Gradient Calibration for Single-Positive Multi-Label Learning in Remote Sensing Image Scene Classification
Chair of Data Science in Earth Observation, Technical University of Munich (TUM), and Munich Center for Machine Learning (MCML)（地球观测数据科学主任，慕尼黑技术大学（TUM）和慕尼黑机器学习中心（MCML））；Department of Information Engineering and Computer Science, University of Trento（信息工程与计算机科学系，特伦托大学）
ChangeQuery: Advancing Remote Sensing Change Analysis for Natural and Human-Induced Disasters from Visual Detection to Semantic Understanding
School of Computer Science and Technology and the Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University（计算机科学与技术学院和教育部智能网络与网络安全重点实验室，西安交通大学）；State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences（遥感与数字地球国家重点实验室，航空信息研究所，中国科学院）；State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University（测绘遥感信息工程国家重点实验室，武汉大学）；Helmholtz-Zentrum Dresden-Rossendorf（德累斯顿-罗斯托克研究所）；Lancaster Environment Centre, Lancaster University（兰卡斯特大学环境研究中心）；Faculty of Electrical and Computer Engineering, University of Iceland（冰岛大学电气与计算机工程学院）；School of Information and Communication Technology, Griffith University（格里菲斯大学信息与通信技术学院）
PolyFootNet: Extracting Polygonal Building Footprints in Off-Nadir Remote Sensing Images
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院航空信息研究所）；School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences（中国科学院大学电子电气与通信工程学院）；Applied Machine Learning Lab, School of Data Science, City University of Hong Kong（香港城市大学数据科学学院应用机器学习实验室）
GAIA: A Global, Multi-modal, Multi-scale Vision-Language Dataset for Remote Sensing Image Analysis
Orion Lab, School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens（奥里昂实验室，农村测绘与地理信息工程学院，希腊雅典国家技术大学）；Institute of Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens（天文、天体物理、空间应用与遥感研究所，希腊雅典国家天文台）；Department of Informatics and Telematics, Harokopio University of Athens（信息与电信技术系，雅典霍罗科皮欧大学）；Chair of Data Science in Earth Observation, Technical University of Munich（地球观测数据科学教授职位，慕尼黑技术大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）；Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin（电气工程与计算机科学系，柏林技术大学）；BIFOLD - Berlin Institute for the Foundations of Learning and Data（柏林学习与数据基础研究所）
JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answering
Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University（清华大学电子工程系，北京信息科学与技术国家研究中心）；Chang Guang Satellite Technology Co., Ltd. (CGSTL)（长光卫星技术股份有限公司）；College of Communications Engineering, Army Engineering University of PLA（中国人民解放军陆军工程大学通信工程学院）
OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents
Mohamed bin Zayed University of Artificial Intelligence（Mohamed bin Zayed人工智能大学）；IBM Research（IBM研究院）；Linköping University（林霍姆斯大学）；Technical University Munich（慕尼黑技术大学）；Australian National University（澳大利亚国立大学）
