arXiv AI

AI vs Human Expert Reasoning: Assessing Agreements in Building Typology Predictions based on Street View Imagery

arXiv:2607. 14756v1 Announce Type: new Abstract: This research investigates the potential of Vision-Language Models (VLMs) to infer building typologies: Construction, Current Use, and Storeys from Google Street View (GSV) images.

arXiv AI

Sep 1

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

arXiv:2506.09557v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorat...

By Zhaoyang Wei, Bowen Jiang, Xumeng Han, Jiashu Li, Xuehui Yu, Yuling Liu, Guorong Li, Zhenjun Han, Jianbin Jiao

llms reinforcement-learning multimodal benchmarks safety

arXiv AI

Aug 12

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

arXiv:2608. 10954v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates significantly in complex scenes under adverse conditions.

By Zhaoyang Wei, Bowen Jiang, Xumeng Han, Jiashu Li, Xuehui Yu, Yuling Liu, Guorong Li, Zhenjun Han, Jianbin Jiao

llms reinforcement-learning multimodal benchmarks safety

arXiv Machine Learning

Aug 21

From Street View Imagery to Street Quality Indicators: Vision Language Inference for the Suburban 15-minute City

arXiv:2608. 20026v1 Announce Type: cross Abstract: Streetscape quality has become a central concern in contemporary urban planning, particularly within the framework of the pedestrian-friendly 15-minute city, where walkability and public-space quality are increasingly recognized as key determinants of urban performance.

By Joan Perez, Giovanni Fusco

llms multimodal

arXiv AI

Jun 17

m2sv: A Scalable Benchmark for Map-to-Street-View Spatial Reasoning

arXiv:2601. 19099v2 Announce Type: replace-cross Abstract: Vision--language models (VLMs) achieve strong performance on many multimodal benchmarks but remain brittle on spatial reasoning tasks that require aligning abstract overhead representations with egocentric views.

By Yosub Shin, Michael Buriek, Igor Molybog

llms reinforcement-learning fine-tuning multimodal benchmarks safety

arXiv AI

Jul 20

DrawingVQA: A Real-World Benchmark for Multi-Depth Visual-Textual Reasoning on Construction Drawings

arXiv:2607. 15418v1 Announce Type: new Abstract: We introduce DrawingVQA, the first benchmark designed to evaluate multimodal large language models (MLLMs) on real-world construction drawings -- a core media in architecture, civil, and many other engineering practices.

By Yoonhwa Jung, Junryu Fu, Mani Golparvar-Fard

llms multimodal benchmarks

arXiv Machine Learning

Jul 2

VisReason: A Large-Scale Dataset for Visual Chain-of-Thought Reasoning

arXiv:2511. 17731v2 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting has proven remarkably effective for eliciting complex reasoning in large language models (LLMs).

By Lingxiao Li, Yifan Wang, Xinyan Gao, Chen Tang, Xiangyu Yue, Chenyu You

llms fine-tuning multimodal benchmarks safety

arXiv AI

Jun 16

UrbanWell: Benchmarking Multimodal Large Language Models for Spatio-Temporal Urban Wellbeing Analytics

arXiv:2606. 15890v1 Announce Type: new Abstract: Understanding urban wellbeing from multimodal data requires integrating heterogeneous spatial and temporal signals, posing significant challenges for current multimodal large language models (MLLMs).

By Yanxin Xi, Xiang Su, Jie Feng, Yu Liu, Sasu Tarkoma, Pan Hui

llms multimodal benchmarks safety

arXiv AI

Jul 16

Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling

arXiv:2607. 13558v1 Announce Type: new Abstract: Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and environmental monitoring.

By Xixuan Hao, Yutian Jiang, Jiabo Liu, Yihang Yang, Guangyin Jin, Song Gao, Yuxuan Liang

rag agents reinforcement-learning multimodal

arXiv AI

Jun 11

Synthetic Homes: A Multimodal Generative AI Pipeline for Residential Building Data Generation under Data Scarcity

arXiv:2509. 09794v5 Announce Type: replace Abstract: Computational models have emerged as powerful tools for multi-scale energy modeling research at the building and urban scale, supporting data-driven analysis across building and urban energy systems.

By Jackson Eshbaugh, Chetan Tiwari, Jorge Silveyra

llms multimodal safety

arXiv AI

Jul 15

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607. 12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models.

By Shelley Cazares

llms agents fine-tuning multimodal benchmarks

arXiv AI

Aug 24

GeoExplain: Multimodal Reasoning based on Hierarchy of Visual Information in Street View

arXiv:2506.16633v3 Announce Type: replace-cross Abstract: Multimodal reasoning is a process of understanding, integrating and inferring information across different data modalities. It has recently a...

By Fenghua Cheng, Jinxiang Wang, Sen Wang, Zi Huang, Xue Li

multimodal

arXiv AI

Jul 9

Thinking Ahead: Foresight Intelligence in MLLMs and World Model

arXiv:2511. 18735v3 Announce Type: replace-cross Abstract: In this work, we define Foresight Intelligence as the capability to anticipate and interpret future events-an ability essential for applications such as autonomous driving, yet largely overlooked by existing research.

By Zhantao Gong, Liaoyuan Fan, Qing Guo, Xun Xu, Xulei Yang, Shijie Li

llms agents robotics fine-tuning multimodal benchmarks

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