Cover Image

Text as Images: Can Multimodal Large Language Models Follow Printed Instructions in Pixels?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Xiujun, Lu, Yujie, Gan, Zhe, Gao, Jianfeng, Wang, William Yang, Choi, Yejin
Format:	Preprint
Published:	2023
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Text to Pixel: Advancing Long-Context Understanding in MLLMs
by: Lu, Yujie, et al.
Published: (2024)

MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMs
by: Qian, Yusu, et al.
Published: (2024)

Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?
by: Fu, Xingyu, et al.
Published: (2024)

Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models
by: Huang, Yupan, et al.
Published: (2023)

WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences
by: Lu, Yujie, et al.
Published: (2024)

Guiding Instruction-based Image Editing via Multimodal Large Language Models
by: Fu, Tsu-Jui, et al.
Published: (2023)

Instruction-Following Evaluation of Large Vision-Language Models
by: Shiono, Daiki, et al.
Published: (2025)

MMRQA: Signal-Enhanced Multimodal Large Language Models for MRI Quality Assessment
by: Jia, Fankai, et al.
Published: (2025)

Text-Printed Image: Bridging the Image-Text Modality Gap for Text-centric Training of Large Vision-Language Models
by: Yamabe, Shojiro, et al.
Published: (2025)

Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing
by: Qian, Yusu, et al.
Published: (2025)

How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts
by: Qian, Yusu, et al.
Published: (2024)

Can Large Vision-Language Models Understand Multimodal Sarcasm?
by: Wang, Xinyu, et al.
Published: (2025)

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation
by: Wu, Mengyang, et al.
Published: (2024)

Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models
by: Gan, Woody Haosheng, et al.
Published: (2025)

Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters
by: Wang, Weizhi, et al.
Published: (2024)

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
by: Wang, Weiyun, et al.
Published: (2024)

ImageChain: Advancing Sequential Image-to-Text Reasoning in Multimodal Large Language Models
by: Villegas, Danae Sánchez, et al.
Published: (2025)

Reading, Not Thinking: Understanding and Bridging the Modality Gap When Text Becomes Pixels in Multimodal LLMs
by: Sun, Kaiser, et al.
Published: (2026)

Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models
by: Zhou, Qiji, et al.
Published: (2024)

Autoregressive Pre-Training on Pixels and Texts
by: Chai, Yekun, et al.
Published: (2024)

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

ScImage: How Good Are Multimodal Large Language Models at Scientific Text-to-Image Generation?
by: Zhang, Leixin, et al.
Published: (2024)

Looking Beyond Text: Reducing Language bias in Large Vision-Language Models via Multimodal Dual-Attention and Soft-Image Guidance
by: Zhao, Haozhe, et al.
Published: (2024)

Humor in Pixels: Benchmarking Large Multimodal Models Understanding of Online Comics
by: Ryan, Yuriel, et al.
Published: (2025)

Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
by: Li, Bin, et al.
Published: (2025)

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
by: Zhang, Shaolei, et al.
Published: (2025)

From Pixels to Tokens: Revisiting Object Hallucinations in Large Vision-Language Models
by: Shang, Yuying, et al.
Published: (2024)

Who Evaluates the Evaluations? Objectively Scoring Text-to-Image Prompt Coherence Metrics with T2IScoreScore (TS2)
by: Saxon, Michael, et al.
Published: (2024)

Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation
by: Zhang, Yuhui, et al.
Published: (2023)

AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception
by: Huang, Yipo, et al.
Published: (2024)

LLAVADI: What Matters For Multimodal Large Language Models Distillation
by: Xu, Shilin, et al.
Published: (2024)

LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
by: Zhang, Yanzhe, et al.
Published: (2023)

MULTI: Multimodal Understanding Leaderboard with Text and Images
by: Zhu, Zichen, et al.
Published: (2024)

The Impact of Image Resolution on Biomedical Multimodal Large Language Models
by: Chen, Liangyu, et al.
Published: (2025)

Incentivizing Reasoning for Advanced Instruction-Following of Large Language Models
by: Qin, Yulei, et al.
Published: (2025)

BLINK: Multimodal Large Language Models Can See but Not Perceive
by: Fu, Xingyu, et al.
Published: (2024)

What Changed? Detecting and Evaluating Instruction-Guided Image Edits with Multimodal Large Language Models
by: Baraldi, Lorenzo, et al.
Published: (2025)

A Survey on Benchmarks of Multimodal Large Language Models
by: Li, Jian, et al.
Published: (2024)

A High-Quality Text-Rich Image Instruction Tuning Dataset via Hybrid Instruction Generation
by: Zhou, Shijie, et al.
Published: (2024)

From Reasoning to Pixels: Benchmarking the Alignment Gap in Unified Multimodal Models
by: Yang, Cheng, et al.
Published: (2026)