Saved in:
| Main Authors: | Liu, Ming, Chen, Hao, Wang, Jindong, Zhang, Wensheng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.09818 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MIMO: A medical vision language model with visual referring multimodal input and pixel grounding multimodal output
by: Chen, Yanyuan, et al.
Published: (2025)
by: Chen, Yanyuan, et al.
Published: (2025)
Is Your Video Language Model a Reliable Judge?
by: Liu, Ming, et al.
Published: (2025)
by: Liu, Ming, et al.
Published: (2025)
Are vision language models robust to uncertain inputs?
by: Wang, Xi, et al.
Published: (2025)
by: Wang, Xi, et al.
Published: (2025)
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation
by: Xu, Lijian, et al.
Published: (2024)
by: Xu, Lijian, et al.
Published: (2024)
Assessing the alignment between infants' visual and linguistic experience using multimodal language models
by: Tan, Alvin Wei Ming, et al.
Published: (2025)
by: Tan, Alvin Wei Ming, et al.
Published: (2025)
When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
by: Zhang, Ruixuan, et al.
Published: (2025)
by: Zhang, Ruixuan, et al.
Published: (2025)
Wan-R1: Verifiable-Reinforcement Learning for Video Reasoning
by: Liu, Ming, et al.
Published: (2026)
by: Liu, Ming, et al.
Published: (2026)
SJTU:Spatial judgments in multimodal models towards unified segmentation through coordinate detection
by: Chae, Joongwon, et al.
Published: (2024)
by: Chae, Joongwon, et al.
Published: (2024)
SalsaAgent: A multimodal embodied language model for interactive dance generation
by: Yazdian, Payam Jome, et al.
Published: (2026)
by: Yazdian, Payam Jome, et al.
Published: (2026)
Buffer replay enhances the robustness of multimodal learning under missing-modality
by: Zhu, Hongye, et al.
Published: (2025)
by: Zhu, Hongye, et al.
Published: (2025)
In-context learning enables multimodal large language models to classify cancer pathology images
by: Ferber, Dyke, et al.
Published: (2024)
by: Ferber, Dyke, et al.
Published: (2024)
A benchmark multimodal oro-dental dataset for large vision-language models
by: Lv, Haoxin, et al.
Published: (2025)
by: Lv, Haoxin, et al.
Published: (2025)
Chain-of-Caption: Training-free improvement of multimodal large language model on referring expression comprehension
by: Pang, Yik Lung, et al.
Published: (2026)
by: Pang, Yik Lung, et al.
Published: (2026)
Evaluating point-light biological motion in multimodal large language models
by: Kadambi, Akila, et al.
Published: (2025)
by: Kadambi, Akila, et al.
Published: (2025)
MULTIAQUA: A multimodal maritime dataset and robust training strategies for multimodal semantic segmentation
by: Muhovič, Jon, et al.
Published: (2025)
by: Muhovič, Jon, et al.
Published: (2025)
Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models
by: Padlewski, Piotr, et al.
Published: (2024)
by: Padlewski, Piotr, et al.
Published: (2024)
GPT-4o: Visual perception performance of multimodal large language models in piglet activity understanding
by: Wu, Yiqi, et al.
Published: (2024)
by: Wu, Yiqi, et al.
Published: (2024)
Finetune Like You Pretrain: Boosting Zero-shot Adversarial Robustness in Vision-language Models
by: Xing, Songlong, et al.
Published: (2026)
by: Xing, Songlong, et al.
Published: (2026)
Attacks on multimodal models
by: Iablochnikov, Viacheslav, et al.
Published: (2024)
by: Iablochnikov, Viacheslav, et al.
Published: (2024)
Elucidating the design space of language models for image generation
by: Liu, Xuantong, et al.
Published: (2024)
by: Liu, Xuantong, et al.
Published: (2024)
What do vision-language models see in the context? Investigating multimodal in-context learning
by: Santos, Gabriel O. dos, et al.
Published: (2025)
by: Santos, Gabriel O. dos, et al.
Published: (2025)
Self-Ensemble Post Learning for Noisy Domain Generalization
by: Lu, Wang, et al.
Published: (2025)
by: Lu, Wang, et al.
Published: (2025)
Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation
by: Liu, Xiaohong, et al.
Published: (2024)
by: Liu, Xiaohong, et al.
Published: (2024)
OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection network
by: Zhao, Tiancheng, et al.
Published: (2022)
by: Zhao, Tiancheng, et al.
Published: (2022)
Corruption-Aware Training of Latent Video Diffusion Models for Robust Text-to-Video Generation
by: Maduabuchi, Chika, et al.
Published: (2025)
by: Maduabuchi, Chika, et al.
Published: (2025)
Animalbooth: multimodal feature enhancement for animal subject personalization
by: Liu, Chen, et al.
Published: (2025)
by: Liu, Chen, et al.
Published: (2025)
Improving automatic detection of driver fatigue and distraction using machine learning
by: Wu, Dongjiang
Published: (2024)
by: Wu, Dongjiang
Published: (2024)
Natural Reflection Backdoor Attack on Vision Language Model for Autonomous Driving
by: Liu, Ming, et al.
Published: (2025)
by: Liu, Ming, et al.
Published: (2025)
Multi-instance robust fitting for non-classical geometric models
by: Zhang, Zongliang, et al.
Published: (2026)
by: Zhang, Zongliang, et al.
Published: (2026)
Enhancing the vision-language foundation model with key semantic knowledge-emphasized report refinement
by: Huang, Weijian, et al.
Published: (2024)
by: Huang, Weijian, et al.
Published: (2024)
Bias-constrained multimodal intelligence for equitable and reliable clinical AI
by: Li, Cheng, et al.
Published: (2026)
by: Li, Cheng, et al.
Published: (2026)
Research on target detection method of distracted driving behavior based on improved YOLOv8
by: Shen, Shiquan, et al.
Published: (2024)
by: Shen, Shiquan, et al.
Published: (2024)
MedVL-SAM2: A unified 3D medical vision-language model for multimodal reasoning and prompt-driven segmentation
by: Xing, Yang, et al.
Published: (2026)
by: Xing, Yang, et al.
Published: (2026)
Human-like object concept representations emerge naturally in multimodal large language models
by: Du, Changde, et al.
Published: (2024)
by: Du, Changde, et al.
Published: (2024)
SAMIR, an efficient registration framework via robust feature learning from SAM
by: He, Yue, et al.
Published: (2025)
by: He, Yue, et al.
Published: (2025)
SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival
by: Pan, Liangrui, et al.
Published: (2024)
by: Pan, Liangrui, et al.
Published: (2024)
A multimodal vision foundation model for generalizable knee pathology
by: Yu, Kang, et al.
Published: (2026)
by: Yu, Kang, et al.
Published: (2026)
A multi-modal vision-language model for generalizable annotation-free pathology localization
by: Yang, Hao, et al.
Published: (2024)
by: Yang, Hao, et al.
Published: (2024)
PM-VIS: High-Performance Box-Supervised Video Instance Segmentation
by: Yang, Zhangjing, et al.
Published: (2024)
by: Yang, Zhangjing, et al.
Published: (2024)
PathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncology
by: Ma, Jiabo, et al.
Published: (2025)
by: Ma, Jiabo, et al.
Published: (2025)
Similar Items
-
MIMO: A medical vision language model with visual referring multimodal input and pixel grounding multimodal output
by: Chen, Yanyuan, et al.
Published: (2025) -
Is Your Video Language Model a Reliable Judge?
by: Liu, Ming, et al.
Published: (2025) -
Are vision language models robust to uncertain inputs?
by: Wang, Xi, et al.
Published: (2025) -
MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation
by: Xu, Lijian, et al.
Published: (2024) -
Assessing the alignment between infants' visual and linguistic experience using multimodal language models
by: Tan, Alvin Wei Ming, et al.
Published: (2025)