Cover Image

MapIQ: Evaluating Multimodal Large Language Models for Map Question Answering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Srivastava, Varun, Lei, Fan, Mukhopadhyay, Srija, Gupta, Vivek, Maciejewski, Ross
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MAPWise: Evaluating Vision-Language Models for Advanced Map Queries
by: Mukhopadhyay, Srija, et al.
Published: (2024)

FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts
by: Singh, Shubhankar, et al.
Published: (2024)

MapVerse: A Benchmark for Geospatial Question Answering on Diverse Real-World Maps
by: Bhat, Sharat, et al.
Published: (2026)

ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering
by: Wu, Yifan, et al.
Published: (2024)

Where do Large Vision-Language Models Look at when Answering Questions?
by: Xing, Xiaoying, et al.
Published: (2025)

VLMT: Vision-Language Multimodal Transformer for Multimodal Multi-hop Question Answering
by: Lim, Qi Zhi, et al.
Published: (2025)

Large Vision-Language Models for Remote Sensing Visual Question Answering
by: Siripong, Surasakdi, et al.
Published: (2024)

Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting
by: Cai, Chen, et al.
Published: (2024)

VisualSimpleQA: A Benchmark for Decoupled Evaluation of Large Vision-Language Models in Fact-Seeking Question Answering
by: Wang, Yanling, et al.
Published: (2025)

Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness
by: Mukhopadhyay, Srija, et al.
Published: (2024)

Multimodal Integration of Human-Like Attention in Visual Question Answering
by: Sood, Ekta, et al.
Published: (2021)

CartoMapQA: A Fundamental Benchmark Dataset Evaluating Vision-Language Models on Cartographic Map Understanding
by: Ung, Huy Quang, et al.
Published: (2025)

Generalizing Visual Question Answering from Synthetic to Human-Written Questions via a Chain of QA with a Large Language Model
by: Kim, Taehee, et al.
Published: (2024)

Weakly Supervised Gaussian Contrastive Grounding with Large Multimodal Models for Video Question Answering
by: Wang, Haibo, et al.
Published: (2024)

Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models
by: An, Wenbin, et al.
Published: (2024)

Design as Desired: Utilizing Visual Question Answering for Multimodal Pre-training
by: Su, Tongkun, et al.
Published: (2024)

DeepSight: Bridging Depth Maps and Language with a Depth-Driven Multimodal Model
by: Yang, Hao, et al.
Published: (2026)

Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering
by: Ha, Cuong Nhat, et al.
Published: (2024)

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping
by: Keleş, Onur, et al.
Published: (2025)

Selectively Answering Visual Questions
by: Eisenschlos, Julian Martin, et al.
Published: (2024)

MOTOR: Multimodal Optimal Transport via Grounded Retrieval in Medical Visual Question Answering
by: Shaaban, Mai A., et al.
Published: (2025)

Overcoming Language Priors for Visual Question Answering Based on Knowledge Distillation
by: Peng, Daowan, et al.
Published: (2025)

Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-rays
by: Cho, Yeongjae, et al.
Published: (2024)

POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering
by: Xu, Yichen, et al.
Published: (2025)

PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering
by: Ding, Yihao, et al.
Published: (2024)

VQA-MHUG: A Gaze Dataset to Study Multimodal Neural Attention in Visual Question Answering
by: Sood, Ekta, et al.
Published: (2021)

Towards Perceiving Small Visual Details in Zero-shot Visual Question Answering with Multimodal LLMs
by: Zhang, Jiarui, et al.
Published: (2023)

Improving Multimodal Large Language Models Using Continual Learning
by: Srivastava, Shikhar, et al.
Published: (2024)

WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering
by: Zhu, Yingjian, et al.
Published: (2026)

ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models
by: Tu, Yahan, et al.
Published: (2024)

EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models
by: Xing, Bohao, et al.
Published: (2025)

Evaluating Multimodal Large Language Models on Vertically Written Japanese Text
by: Sasagawa, Keito, et al.
Published: (2025)

Benchmarking Retrieval-Augmented Multimodal Generation for Document Question Answering
by: Dong, Kuicai, et al.
Published: (2025)

SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers
by: Pramanick, Shraman, et al.
Published: (2024)

Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Survey
by: Kuang, Jiayi, et al.
Published: (2024)

EVQAScore: A Fine-grained Metric for Video Question Answering Data Quality Evaluation
by: Liang, Hao, et al.
Published: (2024)

Prophet: Prompting Large Language Models with Complementary Answer Heuristics for Knowledge-based Visual Question Answering
by: Yu, Zhou, et al.
Published: (2023)

End-to-End Navigation with Vision Language Models: Transforming Spatial Reasoning into Question-Answering
by: Goetting, Dylan, et al.
Published: (2024)

AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models
by: Wu, Yuhang, et al.
Published: (2024)

Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations
by: Ford, James, et al.
Published: (2024)