Cover Image

SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tang, Zhenwei, Jiao, Difan, Yang, Blair, Anderson, Ashton
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multimodal Causal Reasoning Benchmark: Challenging Vision Large Language Models to Discern Causal Links Across Modalities
by: Li, Zhiyuan, et al.
Published: (2024)

Remodeling Semantic Relationships in Vision-Language Fine-Tuning
by: Wu, Xiangyang, et al.
Published: (2025)

ThinkTwice: Jointly Optimizing Large Language Models for Reasoning and Self-Refinement
by: Jiao, Difan, et al.
Published: (2026)

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction
by: Tang, Hongyi, et al.
Published: (2026)

MM-MoralBench: A MultiModal Moral Evaluation Benchmark for Large Vision-Language Models
by: Yan, Bei, et al.
Published: (2024)

Are Unified Vision-Language Models Necessary: Generalization Across Understanding and Generation
by: Zhang, Jihai, et al.
Published: (2025)

MBQ: Modality-Balanced Quantization for Large Vision-Language Models
by: Li, Shiyao, et al.
Published: (2024)

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models
by: Xu, Juangui, et al.
Published: (2025)

FRIEDA: Benchmarking Multi-Step Cartographic Reasoning in Vision-Language Models
by: Pyo, Jiyoon, et al.
Published: (2025)

Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language Models
by: Yan, Hanqi, et al.
Published: (2025)

How Do Vision-Language Models Process Conflicting Information Across Modalities?
by: Hua, Tianze, et al.
Published: (2025)

Freeze and Reveal: Exposing Modality Bias in Vision-Language Models
by: Kavuri, Vivek Hruday, et al.
Published: (2025)

Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models
by: Wang, Zhiqiang, et al.
Published: (2026)

GLIMPSE: Holistic Cross-Modal Explainability for Large Vision-Language Models
by: Shen, Guanxi
Published: (2025)

VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
by: Qin, Guangshuo, et al.
Published: (2026)

EchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models
by: Yuan, Botai, et al.
Published: (2025)

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models
by: Wang, JiYang, et al.
Published: (2026)

XModBench: Benchmarking Cross-Modal Capabilities and Consistency in Omni-Language Models
by: Wang, Xingrui, et al.
Published: (2025)

OODBench: Out-of-Distribution Benchmark for Large Vision-Language Models
by: Lin, Ling, et al.
Published: (2026)

SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals
by: Lin, Zihang, et al.
Published: (2026)

Arbitrary Data as Images: Fusion of Patient Data Across Modalities and Irregular Intervals with Vision Transformers
by: Tölle, Malte, et al.
Published: (2025)

Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language Models
by: Peng, Wei, et al.
Published: (2025)

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
by: Zhong, Yi, et al.
Published: (2026)

A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks
by: Jung, Hoin, et al.
Published: (2024)

CompareBench: A Benchmark for Visual Comparison Reasoning in Vision-Language Models
by: Cai, Jie, et al.
Published: (2025)

HoliSafe: Holistic Safety Benchmarking and Modeling for Vision-Language Model
by: Lee, Youngwan, et al.
Published: (2025)

SUREON: A Benchmark and Vision-Language-Model for Surgical Reasoning
by: Perez, Alejandra, et al.
Published: (2026)

ATA: Bridging Implicit Reasoning with Attention-Guided and Action-Guided Inference for Vision-Language Action Models
by: Yang, Cheng, et al.
Published: (2026)

When Language Overwrites Vision: Over-Alignment and Geometric Debiasing in Vision-Language Models
by: Saini, Harshvardhan, et al.
Published: (2026)

On Robustness of Vision-Language-Action Model against Multi-Modal Perturbations
by: Guo, Jianing, et al.
Published: (2025)

Rice-VL: Evaluating Vision-Language Models for Cultural Understanding Across ASEAN Countries
by: Pranav, Tushar, et al.
Published: (2025)

All in One: Exploring Unified Vision-Language Tracking with Multi-Modal Alignment
by: Zhang, Chunhui, et al.
Published: (2023)

SpaceMind: Camera-Guided Modality Fusion for Spatial Reasoning in Vision-Language Models
by: Zhao, Ruosen, et al.
Published: (2025)

Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Model
by: Feng, Qianhan, et al.
Published: (2024)

Benchmarking Vision Language Models for Cultural Understanding
by: Nayak, Shravan, et al.
Published: (2024)

Multi-Modal Adapter for Vision-Language Models
by: Seputis, Dominykas, et al.
Published: (2024)

Hyperbolic and Evidence-Prioritized Experts for Large Vision-Language Models
by: Zhou, Zijie, et al.
Published: (2026)

IDEATOR: Jailbreaking and Benchmarking Large Vision-Language Models Using Themselves
by: Wang, Ruofan, et al.
Published: (2024)

Image2Struct: Benchmarking Structure Extraction for Vision-Language Models
by: Roberts, Josselin Somerville, et al.
Published: (2024)

ArchSIBench: Benchmarking the Architectural Spatial Intelligence of Vision-Language Models
by: Shen, Qirui, et al.
Published: (2026)