How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?
Fuente:
arXiv
Saved in:
| Main Authors: | Ming, Yifei, Li, Yixuan |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
by: Ming, Yifei, et al.
Published: (2024)
by: Ming, Yifei, et al.
Published: (2024)
Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
by: Miyai, Atsuyuki, et al.
Published: (2024)
by: Miyai, Atsuyuki, et al.
Published: (2024)
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
by: Yu, Geng, et al.
Published: (2024)
by: Yu, Geng, et al.
Published: (2024)
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
by: Zhou, Zhi, et al.
Published: (2024)
by: Zhou, Zhi, et al.
Published: (2024)
Accurately Classifying Out-Of-Distribution Data in Facial Recognition
by: Barone, Gianluca, et al.
Published: (2024)
by: Barone, Gianluca, et al.
Published: (2024)
Generalized Out-of-Distribution Detection: A Survey
by: Yang, Jingkang, et al.
Published: (2021)
by: Yang, Jingkang, et al.
Published: (2021)
You Never Know: Quantization Induces Inconsistent Biases in Vision-Language Foundation Models
by: Slyman, Eric, et al.
Published: (2024)
by: Slyman, Eric, et al.
Published: (2024)
T-QPM: Enabling Temporal Out-Of-Distribution Detection and Domain Generalization for Vision-Language Models in Open-World
by: Naiknaware, Aditi, et al.
Published: (2026)
by: Naiknaware, Aditi, et al.
Published: (2026)
FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
by: Zheng, Weiying, et al.
Published: (2025)
by: Zheng, Weiying, et al.
Published: (2025)
Rethinking Fine-Tuning: Unlocking Hidden Capabilities in Vision-Language Models
by: Zhang, Mingyuan, et al.
Published: (2025)
by: Zhang, Mingyuan, et al.
Published: (2025)
On the Learnability of Out-of-distribution Detection
by: Fang, Zhen, et al.
Published: (2024)
by: Fang, Zhen, et al.
Published: (2024)
On the Detection of Anomalous or Out-Of-Distribution Data in Vision Models Using Statistical Techniques
by: O'Mahony, Laura, et al.
Published: (2024)
by: O'Mahony, Laura, et al.
Published: (2024)
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
Fairness-Aware Fine-Tuning of Vision-Language Models for Medical Glaucoma Diagnosis
by: Gu, Zijian, et al.
Published: (2025)
by: Gu, Zijian, et al.
Published: (2025)
Vision-Language Model Fine-Tuning via Simple Parameter-Efficient Modification
by: Li, Ming, et al.
Published: (2024)
by: Li, Ming, et al.
Published: (2024)
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
by: Li, Fanfei, et al.
Published: (2025)
by: Li, Fanfei, et al.
Published: (2025)
OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
by: Zhang, Jingyang, et al.
Published: (2023)
by: Zhang, Jingyang, et al.
Published: (2023)
Social Perception of Faces in a Vision-Language Model
by: Hausladen, Carina I., et al.
Published: (2024)
by: Hausladen, Carina I., et al.
Published: (2024)
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning
by: Zhai, Yuexiang, et al.
Published: (2024)
by: Zhai, Yuexiang, et al.
Published: (2024)
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection
by: Zhao, Qinyu, et al.
Published: (2024)
by: Zhao, Qinyu, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark
by: Xin, Yi, et al.
Published: (2024)
by: Xin, Yi, et al.
Published: (2024)
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
by: Jie, Shibo, et al.
Published: (2024)
by: Jie, Shibo, et al.
Published: (2024)
Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models
by: Peng, Bo, et al.
Published: (2026)
by: Peng, Bo, et al.
Published: (2026)
pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)
by: Ghiasvand, Sajjad, et al.
Published: (2025)
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
Generating Out-Of-Distribution Scenarios Using Language Models
by: Aasi, Erfan, et al.
Published: (2024)
by: Aasi, Erfan, et al.
Published: (2024)
NODI: Out-Of-Distribution Detection with Noise from Diffusion
by: Zhou, Jingqiu, et al.
Published: (2024)
by: Zhou, Jingqiu, et al.
Published: (2024)
Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
by: Yang, Yuzhe, et al.
Published: (2024)
by: Yang, Yuzhe, et al.
Published: (2024)
Activation Subspaces for Out-of-Distribution Detection
by: Zöngür, Barış, et al.
Published: (2025)
by: Zöngür, Barış, et al.
Published: (2025)
Out-of-Distribution Detection with Relative Angles
by: Demirel, Berker, et al.
Published: (2024)
by: Demirel, Berker, et al.
Published: (2024)
Gradient-Regularized Out-of-Distribution Detection
by: Sharifi, Sina, et al.
Published: (2024)
by: Sharifi, Sina, et al.
Published: (2024)
Out-Of-Distribution Detection with Diversification (Provably)
by: Yao, Haiyun, et al.
Published: (2024)
by: Yao, Haiyun, et al.
Published: (2024)
Fine-Tuning a Large Vision-Language Model for Artwork's Scoring and Critique
by: Zhang, Zhehan, et al.
Published: (2026)
by: Zhang, Zhehan, et al.
Published: (2026)
Revisiting Likelihood-Based Out-of-Distribution Detection by Modeling Representations
by: Ding, Yifan, et al.
Published: (2025)
by: Ding, Yifan, et al.
Published: (2025)
Preserving Fairness Generalization in Deepfake Detection
by: Lin, Li, et al.
Published: (2024)
by: Lin, Li, et al.
Published: (2024)
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
by: Zhou, Andy, et al.
Published: (2023)
by: Zhou, Andy, et al.
Published: (2023)
Learning Multi-Manifold Embedding for Out-Of-Distribution Detection
by: Li, Jeng-Lin, et al.
Published: (2024)
by: Li, Jeng-Lin, et al.
Published: (2024)
Semi-Supervised Fine-Tuning of Vision Foundation Models with Content-Style Decomposition
by: Drozdova, Mariia, et al.
Published: (2024)
by: Drozdova, Mariia, et al.
Published: (2024)
Kernelized Sparse Fine-Tuning with Bi-level Parameter Competition for Vision Models
by: Shen, Shufan, et al.
Published: (2025)
by: Shen, Shufan, et al.
Published: (2025)
Utility-Fairness Trade-Offs and How to Find Them
by: Dehdashtian, Sepehr, et al.
Published: (2024)
by: Dehdashtian, Sepehr, et al.
Published: (2024)
Similar Items
-
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
by: Ming, Yifei, et al.
Published: (2024) -
Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
by: Miyai, Atsuyuki, et al.
Published: (2024) -
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
by: Yu, Geng, et al.
Published: (2024) -
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
by: Zhou, Zhi, et al.
Published: (2024) -
Accurately Classifying Out-Of-Distribution Data in Facial Recognition
by: Barone, Gianluca, et al.
Published: (2024)