Cover Image

Towards Calibrated Robust Fine-Tuning of Vision-Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Oh, Changdae, Lim, Hyesu, Kim, Mijoo, Han, Dongyoon, Yun, Sangdoo, Choo, Jaegul, Hauptmann, Alexander, Cheng, Zhi-Qi, Song, Kyungwoo
Format:	Preprint
Published:	2023
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

DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
by: Oh, Changdae, et al.
Published: (2024)

VisualScratchpad: Inference-time Visual Concepts Analysis in Vision Language Models
by: Lim, Hyesu, et al.
Published: (2026)

RL makes MLLMs see better than SFT
by: Song, Junha, et al.
Published: (2025)

Learning to See What You Need: Gaze Attention for Multimodal Large Language Models
by: Song, Junha, et al.
Published: (2026)

Sparse autoencoders reveal selective remapping of visual concepts during adaptation
by: Lim, Hyesu, et al.
Published: (2024)

ConceptScope: Characterizing Dataset Bias via Disentangled Visual Concepts
by: Choi, Jinho, et al.
Published: (2025)

Rotary Position Embedding for Vision Transformer
by: Heo, Byeongho, et al.
Published: (2024)

Robust Adaptation of Foundation Models with Black-Box Visual Prompting
by: Oh, Changdae, et al.
Published: (2024)

Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction
by: Kim, Jang-Hyun, et al.
Published: (2026)

Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning
by: Kim, Donghu, et al.
Published: (2024)

Temporal In-Context Fine-Tuning with Temporal Reasoning for Versatile Control of Video Diffusion Models
by: Kim, Kinam, et al.
Published: (2025)

Uncertainty Calibration with Energy Based Instance-wise Scaling in the Wild Dataset
by: Kim, Mijoo, et al.
Published: (2024)

Devil is in the Detail: Towards Injecting Fine Details of Image Prompt in Image Generation via Conflict-free Guidance and Stratified Attention
by: Jo, Kyungmin, et al.
Published: (2025)

Masking meets Supervision: A Strong Learning Alliance
by: Heo, Byeongho, et al.
Published: (2023)

Mitigating the Linguistic Gap with Phonemic Representations for Robust Cross-lingual Transfer
by: Jung, Haeji, et al.
Published: (2024)

Model Stock: All we need is just a few fine-tuned models
by: Jang, Dong-Hwan, et al.
Published: (2024)

Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments
by: Lee, Heeyoung, et al.
Published: (2024)

Graph Perceiver IO: A General Architecture for Graph Structured Data
by: Bae, Seyun, et al.
Published: (2022)

Match me if you can: Semi-Supervised Semantic Correspondence Learning with Unpaired Images
by: Kim, Jiwon, et al.
Published: (2023)

HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts
by: Kim, Wonjae, et al.
Published: (2024)

What Defines Good Reasoning in LLMs? Dissecting Reasoning Steps with Multi-Aspect Evaluation
by: Do, Heejin, et al.
Published: (2025)

Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control
by: Hwang, Dongyoon, et al.
Published: (2024)

Oops, Wait: Token-Level Signals as a Lens into LLM Reasoning
by: Hwang, Jaehui, et al.
Published: (2026)

Cross-Frame Representation Alignment for Fine-Tuning Video Diffusion Models
by: Hwang, Sungwon, et al.
Published: (2025)

Vector Prism: Animating Vector Graphics by Stratifying Semantic Structure
by: Yun, Jooyeol, et al.
Published: (2025)

Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization
by: Yun, Jooyeol, et al.
Published: (2024)

Token Bottleneck: One Token to Remember Dynamics
by: Kim, Taekyung, et al.
Published: (2025)

Do's and Don'ts: Learning Desirable Skills with Instruction Videos
by: Kim, Hyunseung, et al.
Published: (2024)

Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess
by: Hwang, Dongyoon, et al.
Published: (2025)

Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models
by: Goel, Anmol, et al.
Published: (2026)

Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language Models
by: Park, Minho, et al.
Published: (2024)

P3T: Prototypical Point-level Prompt Tuning with Enhanced Generalization for 3D Vision-Language Models
by: Jung, Geunyoung, et al.
Published: (2026)

PHUMA: Physically-Grounded Humanoid Locomotion Dataset
by: Lee, Kyungmin, et al.
Published: (2025)

Enabling Region-Specific Control via Lassos in Point-Based Colorization
by: Lee, Sanghyeon, et al.
Published: (2024)

Toward Interactive Regional Understanding in Vision-Large Language Models
by: Lee, Jungbeom, et al.
Published: (2024)

Visual Instruction Bottleneck Tuning
by: Oh, Changdae, et al.
Published: (2025)

Don't Let Bandit Feedback Pull Continual LLM-Recommender Updates Off Target
by: Kim, Taesan, et al.
Published: (2026)

Memory-Efficient Fine-Tuning Diffusion Transformers via Dynamic Patch Sampling and Block Skipping
by: Park, Sunghyun, et al.
Published: (2026)

EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
by: Kim, Jinhee, et al.
Published: (2024)

Bones Can't Be Triangles: Accurate and Efficient Vertebrae Keypoint Estimation through Collaborative Error Revision
by: Kim, Jinhee, et al.
Published: (2024)