Cover Image

Conflict Adaptation in Vision-Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Hu, Xiaoyang
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?
by: Lee, Seongyun, et al.
Published: (2024)

Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Models
by: Zhu, Tinghui, et al.
Published: (2024)

Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts
by: Nooralahzadeh, Farhad, et al.
Published: (2026)

Evaluating Vision Language Model Adaptations for Radiology Report Generation in Low-Resource Languages
by: Salmè, Marco, et al.
Published: (2025)

CROPE: Evaluating In-Context Adaptation of Vision and Language Models to Culture-Specific Concepts
by: Nikandrou, Malvina, et al.
Published: (2024)

Rethinking Multilingual Vision-Language Translation: Dataset, Evaluation, and Adaptation
by: Wang, Xintong, et al.
Published: (2025)

Enhancing Vision-Language Few-Shot Adaptation with Negative Learning
by: Zhang, Ce, et al.
Published: (2024)

Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
by: Cahyawijaya, Samuel, et al.
Published: (2026)

CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values
by: Koleilat, Taha, et al.
Published: (2025)

WAON: A Large-Scale Japanese Image-Text Dataset for Cultural Adaptation in Contrastive Vision-Language Models
by: Sugiura, Issa, et al.
Published: (2025)

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models
by: Li, Bozhou, et al.
Published: (2025)

Insight Over Sight: Exploring the Vision-Knowledge Conflicts in Multimodal LLMs
by: Liu, Xiaoyuan, et al.
Published: (2024)

General Scene Adaptation for Vision-and-Language Navigation
by: Hong, Haodong, et al.
Published: (2025)

From Heads to Neurons: Causal Attribution and Steering in Multi-Task Vision-Language Models
by: Wang, Qidong, et al.
Published: (2026)

MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation
by: Koleilat, Taha, et al.
Published: (2026)

VALOR-EVAL: Holistic Coverage and Faithfulness Evaluation of Large Vision-Language Models
by: Qiu, Haoyi, et al.
Published: (2024)

Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective
by: Zhang, Yanan, et al.
Published: (2024)

Dream-VL & Dream-VLA: Open Vision-Language and Vision-Language-Action Models with Diffusion Language Model Backbone
by: Ye, Jiacheng, et al.
Published: (2025)

Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
by: Lu, Yifan, et al.
Published: (2025)

Vision Language Models are Confused Tourists
by: Irawan, Patrick Amadeus, et al.
Published: (2025)

Enhancing Large Vision Language Models with Self-Training on Image Comprehension
by: Deng, Yihe, et al.
Published: (2024)

FlightGPT: Towards Generalizable and Interpretable UAV Vision-and-Language Navigation with Vision-Language Models
by: Cai, Hengxing, et al.
Published: (2025)

MASSV: Multimodal Adaptation and Self-Data Distillation for Speculative Decoding of Vision-Language Models
by: Ganesan, Mugilan, et al.
Published: (2025)

Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models
by: Hu, Yushi, et al.
Published: (2023)

TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models
by: Zhang, Junyi, et al.
Published: (2025)

Vision-Language Modeling in PET/CT for Visual Grounding of Positive Findings
by: Huemann, Zachary, et al.
Published: (2025)

Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability
by: Shu, Dong, et al.
Published: (2025)

Natural Language Inference Improves Compositionality in Vision-Language Models
by: Cascante-Bonilla, Paola, et al.
Published: (2024)

Do Vision-Language Models Really Understand Visual Language?
by: Hou, Yifan, et al.
Published: (2024)

Watch Closely: Mitigating Object Hallucinations in Large Vision-Language Models with Disentangled Decoding
by: Ma, Ruiqi, et al.
Published: (2025)

Vision-Language Models Do Not Understand Negation
by: Alhamoud, Kumail, et al.
Published: (2025)

Text Prompt Injection of Vision Language Models
by: Zhu, Ruizhe
Published: (2025)

Evaluating Vision-Language Models for Emotion Recognition
by: Bhattacharyya, Sree, et al.
Published: (2025)

Evaluation of Cultural Competence of Vision-Language Models
by: Yadav, Srishti, et al.
Published: (2025)

Vision Language Models Are Not (Yet) Spelling Correctors
by: Liang, Junhong, et al.
Published: (2025)

Intriguing Properties of Large Language and Vision Models
by: Lee, Young-Jun, et al.
Published: (2024)

ViSpec: Accelerating Vision-Language Models with Vision-Aware Speculative Decoding
by: Kang, Jialiang, et al.
Published: (2025)

SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models
by: Carragher, Peter, et al.
Published: (2025)

How Do Vision-Language Models Process Conflicting Information Across Modalities?
by: Hua, Tianze, et al.
Published: (2025)

CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models
by: Castro, Santiago, et al.
Published: (2024)