Cover Image

Breaking the Limits of Open-Weight CLIP: An Optimization Framework for Self-supervised Fine-tuning of CLIP

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mehta, Anant, Wei, Xiyuan, Chen, Xingyu, Yang, Tianbao
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FastCLIP: A Suite of Optimization Techniques to Accelerate CLIP Training with Limited Resources
by: Wei, Xiyuan, et al.
Published: (2024)

NeuCLIP: Efficient Large-Scale CLIP Training with Neural Normalizer Optimization
by: Wei, Xiyuan, et al.
Published: (2025)

Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
by: Liang, Jian, et al.
Published: (2023)

AdFair-CLIP: Adversarial Fair Contrastive Language-Image Pre-training for Chest X-rays
by: Yi, Chenlang, et al.
Published: (2025)

Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
by: Menghini, Cristina, et al.
Published: (2023)

Fine-tuning CLIP Text Encoders with Two-step Paraphrasing
by: Kim, Hyunjae, et al.
Published: (2024)

TiC-CLIP: Continual Training of CLIP Models
by: Garg, Saurabh, et al.
Published: (2023)

Perturb and Recover: Fine-tuning for Effective Backdoor Removal from CLIP
by: Singh, Naman Deep, et al.
Published: (2024)

Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning
by: Qi, Qi, et al.
Published: (2024)

Plug-in Feedback Self-adaptive Attention in CLIP for Training-free Open-Vocabulary Segmentation
by: Chi, Zhixiang, et al.
Published: (2025)

CLIP-UP: A Simple and Efficient Mixture-of-Experts CLIP Training Recipe with Sparse Upcycling
by: Wang, Xinze, et al.
Published: (2025)

Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning
by: Peleg, Amit, et al.
Published: (2025)

DeCLIP: Decoding CLIP representations for deepfake localization
by: Smeu, Stefan, et al.
Published: (2024)

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

Toward Modality Gap: Vision Prototype Learning for Weakly-supervised Semantic Segmentation with CLIP
by: Xu, Zhongxing, et al.
Published: (2024)

Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
by: Balmaseda, Vicente, et al.
Published: (2025)

IsoCLIP: Decomposing CLIP Projectors for Efficient Intra-modal Alignment
by: Magistri, Simone, et al.
Published: (2026)

FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs
by: Dehdashtian, Sepehr, et al.
Published: (2024)

DiffCLIP: Differential Attention Meets CLIP
by: Hammoud, Hasan Abed Al Kader, et al.
Published: (2025)

VeCLIP: Improving CLIP Training via Visual-enriched Captions
by: Lai, Zhengfeng, et al.
Published: (2023)

MoP-CLIP: A Mixture of Prompt-Tuned CLIP Models for Domain Incremental Learning
by: Nicolas, Julien, et al.
Published: (2023)

Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applications
by: Nguyen, Nghia, et al.
Published: (2024)

FROSTER: Frozen CLIP Is A Strong Teacher for Open-Vocabulary Action Recognition
by: Huang, Xiaohu, et al.
Published: (2024)

CountCLIP -- [Re] Teaching CLIP to Count to Ten
by: Mestha, Harshvardhan, et al.
Published: (2024)

Semantic-aware Adversarial Fine-tuning for CLIP
by: Zhang, Jiacheng, et al.
Published: (2026)

Optimizing CLIP Models for Image Retrieval with Maintained Joint-Embedding Alignment
by: Schall, Konstantin, et al.
Published: (2024)

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding
by: Wang, Haoxiang, et al.
Published: (2023)

AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models
by: Metzen, Jan Hendrik, et al.
Published: (2023)

Online Zero-Shot Classification with CLIP
by: Qian, Qi, et al.
Published: (2024)

ToxicTextCLIP: Text-Based Poisoning and Backdoor Attacks on CLIP Pre-training
by: Yao, Xin, et al.
Published: (2025)

LADA: Scalable Label-Specific CLIP Adapter for Continual Learning
by: Luo, Mao-Lin, et al.
Published: (2025)

SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?
by: Hammoud, Hasan Abed Al Kader, et al.
Published: (2024)

MIP: CLIP-based Image Reconstruction from PEFT Gradients
by: Zhou, Peiheng, et al.
Published: (2024)

Finetuning CLIP to Reason about Pairwise Differences
by: Sam, Dylan, et al.
Published: (2024)

Extract Free Dense Misalignment from CLIP
by: Nam, JeongYeon, et al.
Published: (2024)

Is CLIP ideal? No. Can we fix it? Yes!
by: Kang, Raphi, et al.
Published: (2025)

Detecting AI-Generated Images via CLIP
by: Moskowitz, A. G., et al.
Published: (2024)

External Knowledge Injection for CLIP-Based Class-Incremental Learning
by: Zhou, Da-Wei, et al.
Published: (2025)

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

AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning
by: Xie, Zhen-Hao, et al.
Published: (2026)