Cover Image

Hierarchy-Aware Fine-Tuning of Vision-Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Jiayu, Gangireddy, Rajesh, Akcay, Samet, Cheng, Wei, Hu, Juhua
Format:	Preprint
Published:	2025
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

Confounder-Aware Medical Data Selection for Fine-Tuning Pretrained Vision Models
by: Ji, Anyang, et al.
Published: (2025)

3D-Aware Vision-Language Models Fine-Tuning with Geometric Distillation
by: Lee, Seonho, et al.
Published: (2025)

Towards Calibrated Robust Fine-Tuning of Vision-Language Models
by: Oh, Changdae, et al.
Published: (2023)

Fine-Tuning Vision-Language Models for Visual Navigation Assistance
by: Li, Xiao, et al.
Published: (2025)

Remodeling Semantic Relationships in Vision-Language Fine-Tuning
by: Wu, Xiangyang, et al.
Published: (2025)

FairLLaVA: Fairness-Aware Parameter-Efficient Fine-Tuning for Large Vision-Language Assistants
by: Bhosale, Mahesh, et al.
Published: (2026)

Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning of Vision Language Models
by: Tan, Huajie, et al.
Published: (2025)

Fine-Tuning Vision-Language Model for Automated Engineering Drawing Information Extraction
by: Khan, Muhammad Tayyab, et al.
Published: (2024)

Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language Models
by: Peng, Wei, et al.
Published: (2025)

Efficient Prompt Tuning of Large Vision-Language Model for Fine-Grained Ship Classification
by: Lan, Long, et al.
Published: (2024)

RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models
by: Varma, Maya, et al.
Published: (2024)

Is There Knowledge Left to Extract? Evidence of Fragility in Medically Fine-Tuned Vision-Language Models
by: McLaughlin, Oliver, et al.
Published: (2026)

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models
by: Zhu, Wenhui, et al.
Published: (2025)

Multimodal Carotid Risk Stratification with Large Vision-Language Models: Benchmarking, Fine-Tuning, and Clinical Insights
by: Tsolissou, Daphne, et al.
Published: (2025)

Domain-Aware Fine-Tuning of Foundation Models
by: Kaplan, Ugur Ali, et al.
Published: (2024)

Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
by: Hu, Rui, et al.
Published: (2024)

SAC-ViT: Semantic-Aware Clustering Vision Transformer with Early Exit
by: Hu, Youbing, et al.
Published: (2025)

IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning
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)

Fine-Tuning a Large Vision-Language Model for Artwork's Scoring and Critique
by: Zhang, Zhehan, et al.
Published: (2026)

SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding
by: Luo, Junwei, et al.
Published: (2024)

Efficient Adversarial Training via Criticality-Aware Fine-Tuning
by: Li, Wenyun, et al.
Published: (2026)

EVLP:Learning Unified Embodied Vision-Language Planner with Reinforced Supervised Fine-Tuning
by: Cai, Xinyan, et al.
Published: (2025)

Mitigating the Reasoning Tax in Vision-Language Fine-Tuning with Input-Adaptive Depth Aggregation
by: Ren, Yiming, et al.
Published: (2026)

GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains
by: Wang, Chun, et al.
Published: (2025)

Adversarial Prompt Tuning for Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2023)

Tuning Vision-Language Models with Candidate Labels by Prompt Alignment
by: Zhang, Zhifang, et al.
Published: (2024)

BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning
by: Qian, Zekun, et al.
Published: (2026)

FILA: Fine-Grained Vision Language Models
by: Zhu, Shiding, et al.
Published: (2024)

Zooming into Comics: Region-Aware RL Improves Fine-Grained Comic Understanding in Vision-Language Models
by: Chen, Yule, et al.
Published: (2025)

Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients
by: Xiang, Ziwei, et al.
Published: (2026)

A Visual Semantic Adaptive Watermark grounded by Prefix-Tuning for Large Vision-Language Model
by: Zheng, Qi, et al.
Published: (2026)

MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models
by: Yan, Qiao, et al.
Published: (2025)

Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning
by: Devoto, Alessio, et al.
Published: (2024)

Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
by: Schlarmann, Christian, et al.
Published: (2024)

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2025)

Uncertainty-Aware Evaluation for Vision-Language Models
by: Kostumov, Vasily, et al.
Published: (2024)

Vision-Language Model Fine-Tuning via Simple Parameter-Efficient Modification
by: Li, Ming, et al.
Published: (2024)

Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
by: Kim, Moo Jin, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning Medical Multimodal Large Language Models for Medical Visual Grounding
by: He, Jinlong, et al.
Published: (2024)