Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Peng, Wei, Liu, Kang, Hu, Jianchen, Zhang, Meng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BiomedAP: A Vision-Informed Dual-Anchor Framework with Gated Cross-Modal Fusion for Robust Medical Vision-Language Adaptation
by: Tong, Huanyang, et al.
Published: (2026)
by: Tong, Huanyang, et al.
Published: (2026)
Tuning Vision-Language Models with Candidate Labels by Prompt Alignment
by: Zhang, Zhifang, et al.
Published: (2024)
by: Zhang, Zhifang, et al.
Published: (2024)
Adversarial Prompt Tuning for Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2023)
by: Zhang, Jiaming, et al.
Published: (2023)
Prompt Tuning with Soft Context Sharing for Vision-Language Models
by: Ding, Kun, et al.
Published: (2022)
by: Ding, Kun, et al.
Published: (2022)
BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models
by: Koleilat, Taha, et al.
Published: (2024)
by: Koleilat, Taha, et al.
Published: (2024)
NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2025)
by: Zhang, Jiaming, et al.
Published: (2025)
LPT: Less-overfitting Prompt Tuning for Vision-Language Model
by: Ding, Chenhao, et al.
Published: (2024)
by: Ding, Chenhao, et al.
Published: (2024)
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
by: Zhang, Jiahan, et al.
Published: (2024)
by: Zhang, Jiahan, et al.
Published: (2024)
Hierarchy-Aware Fine-Tuning of Vision-Language Models
by: Li, Jiayu, et al.
Published: (2025)
by: Li, Jiayu, et al.
Published: (2025)
Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained Ship Classification
by: Lan, Long, et al.
Published: (2024)
by: Lan, Long, et al.
Published: (2024)
Physical Prompt Injection Attacks on Large Vision-Language Models
by: Ling, Chen, et al.
Published: (2026)
by: Ling, Chen, et al.
Published: (2026)
Explicit Uncertainty Modeling for Active CLIP Adaptation with Dual Prompt Tuning
by: Wang, Qian-Wei, et al.
Published: (2026)
by: Wang, Qian-Wei, et al.
Published: (2026)
Dynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning
by: Hu, Tao, et al.
Published: (2026)
by: Hu, Tao, et al.
Published: (2026)
Evolving Prompt Adaptation for Vision-Language Models
by: Zhang, Enming, et al.
Published: (2026)
by: Zhang, Enming, et al.
Published: (2026)
BiomedXPro: Prompt Optimization for Explainable Diagnosis with Biomedical Vision Language Models
by: Silva, Kaushitha, et al.
Published: (2025)
by: Silva, Kaushitha, et al.
Published: (2025)
Multimodal Emotion Recognition with Vision-language Prompting and Modality Dropout
by: QI, Anbin, et al.
Published: (2024)
by: QI, Anbin, et al.
Published: (2024)
Prompting Large Vision-Language Models for Compositional Reasoning
by: Ossowski, Timothy, et al.
Published: (2024)
by: Ossowski, Timothy, et al.
Published: (2024)
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning
by: Ghosal, Soumya Suvra, et al.
Published: (2024)
by: Ghosal, Soumya Suvra, et al.
Published: (2024)
CAPT: Confusion-Aware Prompt Tuning for Reducing Vision-Language Misalignment
by: Shao, Maoyuan, et al.
Published: (2026)
by: Shao, Maoyuan, et al.
Published: (2026)
PromptEcho: Annotation-Free Reward from Vision-Language Models for Text-to-Image Reinforcement Learning
by: Liu, Jinlong, et al.
Published: (2026)
by: Liu, Jinlong, et al.
Published: (2026)
Historical Test-time Prompt Tuning for Vision Foundation Models
by: Zhang, Jingyi, et al.
Published: (2024)
by: Zhang, Jingyi, et al.
Published: (2024)
MuDPT: Multi-modal Deep-symphysis Prompt Tuning for Large Pre-trained Vision-Language Models
by: Miao, Yongzhu, et al.
Published: (2023)
by: Miao, Yongzhu, et al.
Published: (2023)
DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosis
by: Saeed, Numan, et al.
Published: (2025)
by: Saeed, Numan, et al.
Published: (2025)
MBQ: Modality-Balanced Quantization for Large Vision-Language Models
by: Li, Shiyao, et al.
Published: (2024)
by: Li, Shiyao, et al.
Published: (2024)
Confounder-Aware Medical Data Selection for Fine-Tuning Pretrained Vision Models
by: Ji, Anyang, et al.
Published: (2025)
by: Ji, Anyang, et al.
Published: (2025)
Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models
by: Hu, Yuanwei, et al.
Published: (2026)
by: Hu, Yuanwei, et al.
Published: (2026)
MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants
by: Bansal, Hritik, et al.
Published: (2024)
by: Bansal, Hritik, et al.
Published: (2024)
LAPT: Label-driven Automated Prompt Tuning for OOD Detection with Vision-Language Models
by: Zhang, Yabin, et al.
Published: (2024)
by: Zhang, Yabin, et al.
Published: (2024)
3D-Aware Vision-Language Models Fine-Tuning with Geometric Distillation
by: Lee, Seonho, et al.
Published: (2025)
by: Lee, Seonho, et al.
Published: (2025)
Does Bigger Mean Better? Comparitive Analysis of CNNs and Biomedical Vision Language Modles in Medical Diagnosis
by: Tong, Ran, et al.
Published: (2025)
by: Tong, Ran, et al.
Published: (2025)
Diagnosing and Repairing Unsafe Channels in Vision-Language Models via Causal Discovery and Dual-Modal Safety Subspace Projection
by: Fu, Jinhu, et al.
Published: (2026)
by: Fu, Jinhu, et al.
Published: (2026)
Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
by: Hu, Rui, et al.
Published: (2024)
by: Hu, Rui, et al.
Published: (2024)
Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models
by: Song, Fei, et al.
Published: (2025)
by: Song, Fei, et al.
Published: (2025)
Unifying Biomedical Vision-Language Expertise: Towards a Generalist Foundation Model via Multi-CLIP Knowledge Distillation
by: Wang, Shansong, et al.
Published: (2025)
by: Wang, Shansong, et al.
Published: (2025)
Adversarial Prompt Distillation for Vision-Language Models
by: Luo, Lin, et al.
Published: (2024)
by: Luo, Lin, et al.
Published: (2024)
VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
by: Qin, Guangshuo, et al.
Published: (2026)
by: Qin, Guangshuo, et al.
Published: (2026)
Fine-Tuning Vision-Language Models for Visual Navigation Assistance
by: Li, Xiao, et al.
Published: (2025)
by: Li, Xiao, et al.
Published: (2025)
TinyLVLM-eHub: Towards Comprehensive and Efficient Evaluation for Large Vision-Language Models
by: Shao, Wenqi, et al.
Published: (2023)
by: Shao, Wenqi, et al.
Published: (2023)
SpaceMind: Camera-Guided Modality Fusion for Spatial Reasoning in Vision-Language Models
by: Zhao, Ruosen, et al.
Published: (2025)
by: Zhao, Ruosen, et al.
Published: (2025)
Refer to Any Segmentation Mask Group With Vision-Language Prompts
by: Cao, Shengcao, et al.
Published: (2025)
by: Cao, Shengcao, et al.
Published: (2025)
Similar Items
-
BiomedAP: A Vision-Informed Dual-Anchor Framework with Gated Cross-Modal Fusion for Robust Medical Vision-Language Adaptation
by: Tong, Huanyang, et al.
Published: (2026) -
Tuning Vision-Language Models with Candidate Labels by Prompt Alignment
by: Zhang, Zhifang, et al.
Published: (2024) -
Adversarial Prompt Tuning for Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2023) -
Prompt Tuning with Soft Context Sharing for Vision-Language Models
by: Ding, Kun, et al.
Published: (2022) -
BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models
by: Koleilat, Taha, et al.
Published: (2024)