Cover Image

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Hong-Tao, Peng, Yuxin, Belongie, Serge, Wei, Xiu-Shen
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation
by: Xu, He-Yang, et al.
Published: (2026)

Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models
by: Hai, Jia-Wei, et al.
Published: (2026)

Taxonomy-Aware Evaluation of Vision-Language Models
by: Snæbjarnarson, Vésteinn, et al.
Published: (2025)

Learning Attribute-Aware Hash Codes for Fine-Grained Image Retrieval via Query Optimization
by: Wang, Peng, et al.
Published: (2025)

Benchmarking Large Vision-Language Models via Directed Scene Graph for Comprehensive Image Captioning
by: Lu, Fan, et al.
Published: (2024)

Resampling Benchmark for Efficient Comprehensive Evaluation of Large Vision-Language Models
by: Suzuki, Teppei, et al.
Published: (2025)

Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model
by: An, Zhaochong, et al.
Published: (2025)

Fine-Grained Evaluation of Large Vision-Language Models in Autonomous Driving
by: Li, Yue, et al.
Published: (2025)

FAVOR-Bench: A Comprehensive Benchmark for Fine-Grained Video Motion Understanding
by: Tu, Chongjun, et al.
Published: (2025)

Enhancing Fine-Grained Image Classifications via Cascaded Vision Language Models
by: Wei, Canshi
Published: (2024)

Zero-Shot Fine-Grained Image Classification Using Large Vision-Language Models
by: Atabuzzaman, Md., et al.
Published: (2025)

Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models
by: Pach, Mateusz, et al.
Published: (2025)

Enhancing Large Vision Language Models with Self-Training on Image Comprehension
by: Deng, Yihe, et al.
Published: (2024)

SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing
by: Xiao, Yicheng, et al.
Published: (2026)

Evaluation of Cultural Competence of Vision-Language Models
by: Yadav, Srishti, et al.
Published: (2025)

Explanatory Instructions: Towards Unified Vision Tasks Understanding and Zero-shot Generalization
by: Shen, Yang, et al.
Published: (2024)

MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
by: Ying, Kaining, et al.
Published: (2024)

African or European Swallow? Benchmarking Large Vision-Language Models for Fine-Grained Object Classification
by: Geigle, Gregor, et al.
Published: (2024)

OmniEarth: A Benchmark for Evaluating Vision-Language Models in Geospatial Tasks
by: Fu, Ronghao, et al.
Published: (2026)

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training
by: Gordon, Lucia, et al.
Published: (2026)

Evaluating Attribute Comprehension in Large Vision-Language Models
by: Zhang, Haiwen, et al.
Published: (2024)

MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
by: Fu, Chaoyou, et al.
Published: (2023)

FRISM: Fine-Grained Reasoning Injection via Subspace-Level Model Merging for Vision-Language Models
by: Huang, Chenyu, et al.
Published: (2026)

FinePOSE: Fine-Grained Prompt-Driven 3D Human Pose Estimation via Diffusion Models
by: Xu, Jinglin, et al.
Published: (2024)

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models
by: Roger, Alexis, et al.
Published: (2025)

A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
by: Xiu, Lixin, et al.
Published: (2026)

MMDocBench: Benchmarking Large Vision-Language Models for Fine-Grained Visual Document Understanding
by: Zhu, Fengbin, et al.
Published: (2024)

EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models
by: Shan, Haozhe, et al.
Published: (2026)

Venus: Benchmarking and Empowering Multimodal Large Language Models for Aesthetic Guidance and Cropping
by: Du, Tianxiang, et al.
Published: (2026)

SliceLens: Fine-Grained and Grounded Error Slice Discovery for Multi-Instance Vision Tasks
by: Zhang, Wei, et al.
Published: (2025)

FineCops-Ref: A new Dataset and Task for Fine-Grained Compositional Referring Expression Comprehension
by: Liu, Junzhuo, et al.
Published: (2024)

EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation
by: Han, Shuhao, et al.
Published: (2024)

New Dataset and Methods for Fine-Grained Compositional Referring Expression Comprehension via Specialist-MLLM Collaboration
by: Yang, Xuzheng, et al.
Published: (2025)

RAIGen: Rare Attribute Identification in Text-to-Image Generative Models
by: Sreelatha, Silpa Vadakkeeveetil, et al.
Published: (2026)

Better Language Models Exhibit Higher Visual Alignment
by: Ruthardt, Jona, et al.
Published: (2024)

Uni-MuMER: Unified Multi-Task Fine-Tuning of Vision-Language Model for Handwritten Mathematical Expression Recognition
by: Li, Yu, et al.
Published: (2025)

VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model
by: Wang, Sibo, et al.
Published: (2024)

IllusionBench+: A Large-scale and Comprehensive Benchmark for Visual Illusion Understanding in Vision-Language Models
by: Zhang, Yiming, et al.
Published: (2025)

Towards Fine-Grained Recognition with Large Visual Language Models: Benchmark and Optimization Strategies
by: Pang, Cong, et al.
Published: (2025)

EyePCR: A Comprehensive Benchmark for Fine-Grained Perception, Knowledge Comprehension and Clinical Reasoning in Ophthalmic Surgery
by: Wang, Gui, et al.
Published: (2025)