Image de couverture de livre

Burn After Reading: Do Multimodal Large Language Models Truly Capture Order of Events in Image Sequences?

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Song, Yingjin, Du, Yupei, Paperno, Denis, Gatt, Albert
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Context-aware Visual Storytelling with Visual Prefix Tuning and Contrastive Learning
par: Song, Yingjin, et autres
Publié: (2024)

From Image Captioning to Visual Storytelling
par: Passadakis, Admitos, et autres
Publié: (2025)

Don't Learn, Ground: A Case for Natural Language Inference with Visual Grounding
par: Ignatev, Daniil, et autres
Publié: (2025)

Common Objects Out of Context (COOCo): Investigating Multimodal Context and Semantic Scene Violations in Referential Communication
par: Merlo, Filippo, et autres
Publié: (2025)

Do Vision-Language Models Truly Perform Vision Reasoning? A Rigorous Study of the Modality Gap
par: Xu, Yige, et autres
Publié: (2026)

Disentangling the Roles of Representation and Selection in Data Pruning
par: Du, Yupei, et autres
Publié: (2025)

Do Multimodal Large Language Models Understand Welding?
par: Khvatskii, Grigorii, et autres
Publié: (2025)

LogicOCR: Do Your Large Multimodal Models Excel at Logical Reasoning on Text-Rich Images?
par: Ye, Maoyuan, et autres
Publié: (2025)

FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
par: Du, Yupei, et autres
Publié: (2023)

WSI-LLaVA: A Multimodal Large Language Model for Whole Slide Image
par: Liang, Yuci, et autres
Publié: (2024)

The Impact of Image Resolution on Biomedical Multimodal Large Language Models
par: Chen, Liangyu, et autres
Publié: (2025)

Do Vision Encoders Truly Explain Object Hallucination?: Mitigating Object Hallucination via Simple Fine-Grained CLIPScore
par: Oh, Hongseok, et autres
Publié: (2025)

Kosmos-G: Generating Images in Context with Multimodal Large Language Models
par: Pan, Xichen, et autres
Publié: (2023)

Do Egocentric Video-Language Models Truly Understand Hand-Object Interactions?
par: Xu, Boshen, et autres
Publié: (2024)

Do Composed Image Retrieval Benchmarks Require Multimodal Composition?
par: Attimonelli, Matteo, et autres
Publié: (2026)

ROAP: A Reading-Order and Attention-Prior Pipeline for Optimizing Layout Transformers in Key Information Extraction
par: Xie, Tingwei, et autres
Publié: (2026)

Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences
par: Wang, Xiyao, et autres
Publié: (2024)

AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception
par: Huang, Yipo, et autres
Publié: (2024)

From Perception to Reasoning: Deep Thinking Empowers Multimodal Large Language Models
par: Zhu, Wenxin, et autres
Publié: (2025)

Understanding Multimodal Procedural Knowledge by Sequencing Multimodal Instructional Manuals
par: Wu, Te-Lin, et autres
Publié: (2021)

Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models
par: Li, Yifan, et autres
Publié: (2024)

RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models
par: Chen, Haoyu, et autres
Publié: (2024)

Correlates of Image Memorability in Vision Encoders: Activations, Attention Entropy, Patch Uniformity and Autoencoder Losses
par: Takmaz, Ece, et autres
Publié: (2025)

II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models
par: Liu, Ziqiang, et autres
Publié: (2024)

Indexing Multimodal Language Models for Large-scale Image Retrieval
par: Tharwat, Bahey, et autres
Publié: (2026)

ChatEXAONEPath: An Expert-level Multimodal Large Language Model for Histopathology Using Whole Slide Images
par: Kim, Sangwook, et autres
Publié: (2025)

Model Composition for Multimodal Large Language Models
par: Chen, Chi, et autres
Publié: (2024)

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation
par: Wu, Mengyang, et autres
Publié: (2024)

ImageChain: Advancing Sequential Image-to-Text Reasoning in Multimodal Large Language Models
par: Villegas, Danae Sánchez, et autres
Publié: (2025)

Looking Beyond Text: Reducing Language bias in Large Vision-Language Models via Multimodal Dual-Attention and Soft-Image Guidance
par: Zhao, Haozhe, et autres
Publié: (2024)

AdaMMS: Model Merging for Heterogeneous Multimodal Large Language Models with Unsupervised Coefficient Optimization
par: Du, Yiyang, et autres
Publié: (2025)

Grounding Partially-Defined Events in Multimodal Data
par: Sanders, Kate, et autres
Publié: (2024)

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images
par: You, Liangliang, et autres
Publié: (2025)

Argus Inspection: Do Multimodal Large Language Models Possess the Eye of Panoptes?
par: Yao, Yang, et autres
Publié: (2025)

The Use of Multimodal Large Language Models to Detect Objects from Thermal Images: Transportation Applications
par: Ashqar, Huthaifa I., et autres
Publié: (2024)

Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language Models
par: Xu, Shilin, et autres
Publié: (2025)

ScImage: How Good Are Multimodal Large Language Models at Scientific Text-to-Image Generation?
par: Zhang, Leixin, et autres
Publié: (2024)

Plug-and-Play Grounding of Reasoning in Multimodal Large Language Models
par: Chen, Jiaxing, et autres
Publié: (2024)

Can Large Vision-Language Models Understand Multimodal Sarcasm?
par: Wang, Xinyu, et autres
Publié: (2025)

LLAVADI: What Matters For Multimodal Large Language Models Distillation
par: Xu, Shilin, et autres
Publié: (2024)