Copertina

CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Jha, Saurav, Gong, Dong, Yao, Lina
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Beyond CLIP Generalization: Against Forward&Backward Forgetting Adapter for Continual Learning of Vision-Language Models
di: Dong, Songlin, et al.
Pubblicazione: (2025)

Continual Learning on CLIP via Incremental Prompt Tuning with Intrinsic Textual Anchors
di: Lu, Haodong, et al.
Pubblicazione: (2025)

fine-CLIP: Enhancing Zero-Shot Fine-Grained Surgical Action Recognition with Vision-Language Models
di: Sharma, Saurav, et al.
Pubblicazione: (2025)

In the Era of Prompt Learning with Vision-Language Models
di: Jha, Ankit
Pubblicazione: (2024)

Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning
di: Wang, Huiyi, et al.
Pubblicazione: (2024)

Mining Your Own Secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models
di: Jha, Saurav, et al.
Pubblicazione: (2024)

CLAP: Contrastive Latent Action Pretraining for Learning Vision-Language-Action Models from Human Videos
di: Zhang, Chubin, et al.
Pubblicazione: (2026)

Anchor-based Robust Finetuning of Vision-Language Models
di: Han, Jinwei, et al.
Pubblicazione: (2024)

CLIP-GS: Unifying Vision-Language Representation with 3D Gaussian Splatting
di: Jiao, Siyu, et al.
Pubblicazione: (2024)

FairCLIP: Harnessing Fairness in Vision-Language Learning
di: Luo, Yan, et al.
Pubblicazione: (2024)

Take Only What You Need: Rank Minimization as an Implicit Forgetting Regularizer in Continual Learning
di: Lu, Haodong, et al.
Pubblicazione: (2024)

AD-CLIP: Adapting Domains in Prompt Space Using CLIP
di: Singha, Mainak, et al.
Pubblicazione: (2023)

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features
di: Sengupta, Saurav, et al.
Pubblicazione: (2025)

ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference
di: Lan, Mengcheng, et al.
Pubblicazione: (2024)

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

MedProbCLIP: Probabilistic Adaptation of Vision-Language Foundation Model for Reliable Radiograph-Report Retrieval
di: Elallaf, Ahmad, et al.
Pubblicazione: (2026)

ProCLIP: Progressive Vision-Language Alignment via LLM-based Embedder
di: Hu, Xiaoxing, et al.
Pubblicazione: (2025)

CLIP-SLA: Parameter-Efficient CLIP Adaptation for Continuous Sign Language Recognition
di: Alyami, Sarah, et al.
Pubblicazione: (2025)

HQ-CLIP: Leveraging Large Vision-Language Models to Create High-Quality Image-Text Datasets and CLIP Models
di: Wei, Zhixiang, et al.
Pubblicazione: (2025)

Diversity Covariance-Aware Prompt Learning for Vision-Language Models
di: Dong, Songlin, et al.
Pubblicazione: (2025)

CosmoCLIP: Generalizing Large Vision-Language Models for Astronomical Imaging
di: Imam, Raza, et al.
Pubblicazione: (2024)

CLIP-VAD: Exploiting Vision-Language Models for Voice Activity Detection
di: Appiani, Andrea, et al.
Pubblicazione: (2024)

RemoteCLIP: A Vision Language Foundation Model for Remote Sensing
di: Liu, Fan, et al.
Pubblicazione: (2023)

DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observation
di: Xiong, Zhitong, et al.
Pubblicazione: (2025)

GLOV: Guided Large Language Models as Implicit Optimizers for Vision Language Models
di: Mirza, M. Jehanzeb, et al.
Pubblicazione: (2024)

Finetuning Vision-Language Models as OCR Systems for Low-Resource Languages: A Case Study of Manchu
di: Chung, Yan Hon Michael, et al.
Pubblicazione: (2025)

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization
di: Zang, Yuhang, et al.
Pubblicazione: (2024)

Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters
di: Yu, Jiazuo, et al.
Pubblicazione: (2024)

CLIP-Adapter: Better Vision-Language Models with Feature Adapters
di: Gao, Peng, et al.
Pubblicazione: (2021)

Joint Vision-Language Social Bias Removal for CLIP
di: Zhang, Haoyu, et al.
Pubblicazione: (2024)

CLIP-HandID: Vision-Language Model for Hand-Based Person Identification
di: Baisa, Nathanael L., et al.
Pubblicazione: (2025)

CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
di: Zhao, Shuai, et al.
Pubblicazione: (2023)

IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware Prompting
di: Fu, Hao, et al.
Pubblicazione: (2025)

Can Vision-Language Models Count? A Synthetic Benchmark and Analysis of Attention-Based Interventions
di: Sengupta, Saurav, et al.
Pubblicazione: (2025)

Enhanced Continual Learning of Vision-Language Models with Model Fusion
di: Gao, Haoyuan, et al.
Pubblicazione: (2025)

CLIP-FSAC++: Few-Shot Anomaly Classification with Anomaly Descriptor Based on CLIP
di: Zuo, Zuo, et al.
Pubblicazione: (2024)

Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning
di: P, Jishnu Jaykumar, et al.
Pubblicazione: (2023)

$β$-CLIP: Text-Conditioned Contrastive Learning for Multi-Granular Vision-Language Alignment
di: Zohra, Fatimah, et al.
Pubblicazione: (2025)

MaskedCLIP: Bridging the Masked and CLIP Space for Semi-Supervised Medical Vision-Language Pre-training
di: Zhu, Lei, et al.
Pubblicazione: (2025)

CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts
di: Cai, Yichao, et al.
Pubblicazione: (2023)