Cover Image

Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Linlan, Cao, Xusheng, Lu, Haori, Liu, Xialei
Format:	Preprint
Published:	2024
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

Generative Multi-modal Models are Good Class-Incremental Learners
by: Cao, Xusheng, et al.
Published: (2024)

Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning
by: Huang, Linlan, et al.
Published: (2025)

Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning
by: Cao, Xusheng, et al.
Published: (2025)

Restoring Forgotten Knowledge in Non-Exemplar Class Incremental Learning through Test-Time Semantic Evolution
by: Lu, Haori, et al.
Published: (2025)

Adaptive Weighted Parameter Fusion with CLIP for Class-Incremental Learning
by: Guo, Juncen, et al.
Published: (2025)

Learning Part Knowledge to Facilitate Category Understanding for Fine-Grained Generalized Category Discovery
by: Wang, Enguang, et al.
Published: (2025)

Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation
by: Xie, Zhengyuan, et al.
Published: (2024)

BOFA: Bridge-Layer Orthogonal Low-Rank Fusion for CLIP-Based Class-Incremental Learning
by: Li, Lan, et al.
Published: (2025)

Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning
by: Zhao, Haifeng, et al.
Published: (2024)

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

Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting
by: Liu, Yuyang, et al.
Published: (2025)

Hierarchical Semantic Tree Anchoring for CLIP-Based Class-Incremental Learning
by: Hu, Tao, et al.
Published: (2025)

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

C3Box: A CLIP-based Class-Incremental Learning Toolbox
by: Sun, Hao, et al.
Published: (2026)

Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning
by: Qi, Zhi-Hong, et al.
Published: (2024)

Task-Adaptive Saliency Guidance for Exemplar-free Class Incremental Learning
by: Liu, Xialei, et al.
Published: (2022)

Future-Proofing Class-Incremental Learning
by: Jodelet, Quentin, et al.
Published: (2024)

Confidence Self-Calibration for Multi-Label Class-Incremental Learning
by: Du, Kaile, et al.
Published: (2024)

Class-Incremental Learning: A Survey
by: Zhou, Da-Wei, et al.
Published: (2023)

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

Cross-Class Feature Augmentation for Class Incremental Learning
by: Kim, Taehoon, et al.
Published: (2023)

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
by: Zhou, Da-Wei, et al.
Published: (2023)

Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt
by: Liu, Chenxi, et al.
Published: (2024)

Improving Forward Compatibility in Class Incremental Learning by Increasing Representation Rank and Feature Richness
by: Kim, Jaeill, et al.
Published: (2024)

One Adapter for All: Towards Unified Representation in Step-Imbalanced Class-Incremental Learning
by: Zhang, Xiaoyan, et al.
Published: (2026)

From Isolation to Integration: Building an Adaptive Expert Forest for Pre-Trained Model-based Class-Incremental Learning
by: Liu, Ruiqi, et al.
Published: (2026)

Grow, Assess, Compress: Adaptive Backbone Scaling for Memory-Efficient Class Incremental Learning
by: Garcia-Castañeda, Adrian, et al.
Published: (2026)

Closing the Oracle Gap: Increment Vector Transformation for Class Incremental Learning
by: Qiu, Zihuan, et al.
Published: (2025)

iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning
by: Fischer, Tom, et al.
Published: (2024)

Effective Decision Boundary Learning for Class Incremental Learning
by: Li, Kunchi, et al.
Published: (2023)

Class-wise Balancing Data Replay for Federated Class-Incremental Learning
by: Qi, Zhuang, et al.
Published: (2025)

Specifying What You Know or Not for Multi-Label Class-Incremental Learning
by: Zhang, Aoting, et al.
Published: (2025)

Stable Routing for Mixture-of-Experts in Class-Incremental Learning
by: Guo, Zirui, et al.
Published: (2026)

P2L-CA: An Effective Parameter Tuning Framework for Rehearsal-Free Multi-Label Class-Incremental Learning
by: Dong, Songlin, et al.
Published: (2026)

GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery
by: Wang, Enguang, et al.
Published: (2024)

Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning
by: Liu, Jiaming, et al.
Published: (2024)

OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning
by: Huang, Wei-Cheng, et al.
Published: (2024)

Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation
by: Kwak, Jihwan, et al.
Published: (2024)

Quantum-Gated Task-interaction Knowledge Distillation for Pre-trained Model-based Class-Incremental Learning
by: Li, Linjie, et al.
Published: (2026)

When Classes Evolve: A Benchmark and Framework for Stage-Aware Class-Incremental Learning
by: Zhang, Zheng, et al.
Published: (2026)