Cover Image

Explaining Multi-modal Large Language Models by Analyzing their Vision Perception

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Giulivi, Loris, Boracchi, Giacomo
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNet
by: Giulivi, Loris, et al.
Published: (2024)

SE3D: A Framework For Saliency Method Evaluation In 3D Imaging
by: Wiśniewski, Mariusz, et al.
Published: (2024)

An expert-driven data generation pipeline for histological images
by: Basla, Roberto, et al.
Published: (2024)

MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model Selection
by: Magri, Luca, et al.
Published: (2025)

Convolutional Set Transformer
by: Chinello, Federico, et al.
Published: (2025)

CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models
by: Cheng, Zihui, et al.
Published: (2024)

Sparks of Explainability: Recent Advancements in Explaining Large Vision Models
by: Fel, Thomas
Published: (2025)

LLMTrack: Semantic Multi-Object Tracking with Multi-modal Large Language Models
by: Liao, Pan, et al.
Published: (2026)

Beyond Static Vision: Scene Dynamic Field Unlocks Intuitive Physics Understanding in Multi-modal Large Language Models
by: Li, Nanxi, et al.
Published: (2026)

DHCP: Detecting Hallucinations by Cross-modal Attention Pattern in Large Vision-Language Models
by: Zhang, Yudong, et al.
Published: (2024)

Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
by: He, Hulingxiao, et al.
Published: (2025)

Temporal-consistent CAMs for Weakly Supervised Video Segmentation in Waste Sorting
by: Marelli, Andrea, et al.
Published: (2025)

PIF: Anomaly detection via preference embedding
by: Leveni, Filippo, et al.
Published: (2025)

Hashing for Structure-based Anomaly Detection
by: Leveni, Filippo, et al.
Published: (2025)

Preference Isolation Forest for Structure-based Anomaly Detection
by: Leveni, Filippo, et al.
Published: (2025)

Multi-modal, Multi-task, Multi-criteria Automatic Evaluation with Vision Language Models
by: Ohi, Masanari, et al.
Published: (2024)

EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents
by: Yang, Rui, et al.
Published: (2025)

MVP-Bench: Can Large Vision--Language Models Conduct Multi-level Visual Perception Like Humans?
by: Li, Guanzhen, et al.
Published: (2024)

Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
by: Li, Yanwei, et al.
Published: (2024)

AUVIC: Adversarial Unlearning of Visual Concepts for Multi-modal Large Language Models
by: Chen, Haokun, et al.
Published: (2025)

MultiEmo-Bench: Multi-label Visual Emotion Analysis for Multi-modal Large Language Models
by: Chen, Tianwei, et al.
Published: (2026)

Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision
by: Walimbe, Soham, et al.
Published: (2025)

Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples
by: Gao, Kuofeng, et al.
Published: (2024)

Advancing Visual Large Language Model for Multi-granular Versatile Perception
by: Xiang, Wentao, et al.
Published: (2025)

ZERO: Industry-ready Vision Foundation Model with Multi-modal Prompts
by: Choi, Sangbum, et al.
Published: (2025)

Visual Hallucinations of Multi-modal Large Language Models
by: Huang, Wen, et al.
Published: (2024)

Revealing Multi-View Hallucination in Large Vision-Language Models
by: Park, Wooje, et al.
Published: (2026)

A Deep Learning Pipeline for Solid Waste Detection in Remote Sensing Images
by: Gibellini, Federico, et al.
Published: (2025)

Learning Emergent Modular Representations in Multi-modality Medical Vision Foundation Models
by: He, Yuting, et al.
Published: (2026)

Explaining multimodal LLMs via intra-modal token interactions
by: Liang, Jiawei, et al.
Published: (2025)

AirCache: Activating Inter-modal Relevancy KV Cache Compression for Efficient Large Vision-Language Model Inference
by: Huang, Kai, et al.
Published: (2025)

Towards Cross-modal Backward-compatible Representation Learning for Vision-Language Models
by: Jang, Young Kyun, et al.
Published: (2024)

FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models
by: Xu, Zhipei, et al.
Published: (2024)

ViSRA: A Video-based Spatial Reasoning Agent for Multi-modal Large Language Models
by: Mou, Tingshu, et al.
Published: (2026)

AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability
by: Zhao, Fei, et al.
Published: (2024)

MIRAGE: A Multi-modal Benchmark for Spatial Perception, Reasoning, and Intelligence
by: Liu, Chonghan, et al.
Published: (2025)

Think Hierarchically, Act Dynamically: Hierarchical Multi-modal Fusion and Reasoning for Vision-and-Language Navigation
by: Yue, Junrong, et al.
Published: (2025)

Medical Large Vision Language Models with Multi-Image Visual Ability
by: Yang, Xikai, et al.
Published: (2025)

PruneHal: Reducing Hallucinations in Multi-modal Large Language Models through Adaptive KV Cache Pruning
by: Sun, Fengyuan, et al.
Published: (2025)

Why Only Text: Empowering Vision-and-Language Navigation with Multi-modal Prompts
by: Hong, Haodong, et al.
Published: (2024)