Cover Image

Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nam, Giung, Heo, Byeongho, Lee, Juho
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AutoFT: Learning an Objective for Robust Fine-Tuning
by: Choi, Caroline, et al.
Published: (2024)

Efficient and Versatile Robust Fine-Tuning of Zero-shot Models
by: Kim, Sungyeon, et al.
Published: (2024)

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

DNNs May Determine Major Properties of Their Outputs Early, with Timing Possibly Driven by Bias
by: Park, Song, et al.
Published: (2025)

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

DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs
by: Kim, Donghyun, et al.
Published: (2024)

StarFT: Robust Fine-tuning of Zero-shot Models via Spuriosity Alignment
by: Kim, Younghyun, et al.
Published: (2025)

WeGeFT: Weight-Generative Fine-Tuning for Multi-Faceted Efficient Adaptation of Large Models
by: Savadikar, Chinmay, et al.
Published: (2023)

Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
by: Li, Kaican, et al.
Published: (2024)

Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance
by: Moufad, Badr, et al.
Published: (2025)

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

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

Similarity of Neural Architectures using Adversarial Attack Transferability
by: Hwang, Jaehui, et al.
Published: (2022)

On the Robustness Tradeoff in Fine-Tuning
by: Li, Kunyang, et al.
Published: (2025)

LoFT: Parameter-Efficient Fine-Tuning for Long-tailed Semi-Supervised Learning in Open-World Scenarios
by: Huang, Zhiyuan, et al.
Published: (2025)

ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation
by: Min, Yunhong, et al.
Published: (2025)

Enhancing Zero-Shot Image Recognition in Vision-Language Models through Human-like Concept Guidance
by: Liu, Hui, et al.
Published: (2025)

Sequential Flow Straightening for Generative Modeling
by: Yoon, Jongmin, et al.
Published: (2024)

AGFT: Alignment-Guided Fine-Tuning for Zero-Shot Adversarial Robustness of Vision-Language Models
by: Cui, Yubo, et al.
Published: (2026)

SWiFT: Soft-Mask Weight Fine-tuning for Bias Mitigation
by: Yan, Junyu, et al.
Published: (2025)

Scratching Visual Transformer's Back with Uniform Attention
by: Hyeon-Woo, Nam, et al.
Published: (2022)

Investigating the Effectiveness of Cross-Attention to Unlock Zero-Shot Editing of Text-to-Video Diffusion Models
by: Motamed, Saman, et al.
Published: (2024)

Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
by: Tian, Junjiao, et al.
Published: (2024)

Let's Split Up: Zero-Shot Classifier Edits for Fine-Grained Video Understanding
by: Liu, Kaiting, et al.
Published: (2026)

Basis-Oriented Low-rank Transfer for Few-Shot and Test-Time Adaptation
by: Park, Junghwan, et al.
Published: (2025)

SAM-PTx: Text-Guided Fine-Tuning of SAM with Parameter-Efficient, Parallel-Text Adapters
by: Jalilian, Shayan, et al.
Published: (2025)

Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Model
by: Cao, Cong, et al.
Published: (2024)

Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning
by: Lee, Yeoreum, et al.
Published: (2025)

FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization
by: Gu, Zhaopeng, et al.
Published: (2024)

Steering Guidance for Personalized Text-to-Image Diffusion Models
by: Park, Sunghyun, et al.
Published: (2025)

A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shot
by: Abdollahzadeh, Milad, et al.
Published: (2023)

AugLoss: A Robust Augmentation-based Fine Tuning Methodology
by: Otstot, Kyle, et al.
Published: (2022)

Contrast-Aware Calibration for Fine-Tuned CLIP: Leveraging Image-Text Alignment
by: Lv, Song-Lin, et al.
Published: (2025)

Context-Aware Zero-Shot Anomaly Detection in Surveillance Using Contrastive and Predictive Spatiotemporal Modeling
by: Khan, Md. Rashid Shahriar, et al.
Published: (2025)

FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations
by: Hsieh, Cheng-Yu, et al.
Published: (2025)

UNCAGE: Contrastive Attention Guidance for Masked Generative Transformers in Text-to-Image Generation
by: Kang, Wonjun, et al.
Published: (2025)

Robust and Generalizable GNN Fine-Tuning via Uncertainty-aware Adapter Learning
by: Jiang, Bo, et al.
Published: (2025)

Domain-Aware Fine-Tuning: Enhancing Neural Network Adaptability
by: Ha, Seokhyeon, et al.
Published: (2023)

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance
by: Mei, Ruo-Syuan, et al.
Published: (2025)

Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness
by: Wang, Sibo, et al.
Published: (2024)