Cover Image

Towards Experience Replay for Class-Incremental Learning in Fully-Binary Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Basso-Bert, Yanis, Molnos, Anca, Lemaire, Romain, Guicquero, William, Dupret, Antoine
Format:	Preprint
Published:	2025
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

Generative Binary Memory: Pseudo-Replay Class-Incremental Learning on Binarized Embeddings
by: Basso-Bert, Yanis, et al.
Published: (2025)

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

End-to-end fully-binarized network design: from Generic Learned Thermometer to Block Pruning
by: Nguyen, Thien, et al.
Published: (2025)

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

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

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

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

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

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

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

ER-FSL: Experience Replay with Feature Subspace Learning for Online Continual Learning
by: Lin, Huiwei
Published: (2024)

CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning
by: Frascaroli, Emanuele, et al.
Published: (2024)

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

A 1Mb mixed-precision quantized encoder for image classification and patch-based compression
by: Nguyen, Van Thien, et al.
Published: (2025)

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

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

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

On Distilling the Displacement Knowledge for Few-Shot Class-Incremental Learning
by: Fang, Pengfei, et al.
Published: (2024)

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

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

A Bag of Tricks for Few-Shot Class-Incremental Learning
by: Roy, Shuvendu, et al.
Published: (2024)

Understanding Imbalanced Forgetting in Rehearsal-Based Class-Incremental Learning
by: Tamajo, Alberto, et al.
Published: (2026)

Scalable Class-Incremental Learning Based on Parametric Neural Collapse
by: Zhang, Chuangxin, et al.
Published: (2025)

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

IDER: IDempotent Experience Replay for Reliable Continual Learning
by: Liu, Zhanwang, et al.
Published: (2026)

12 mJ per Class On-Device Online Few-Shot Class-Incremental Learning
by: Wibowo, Yoga Esa, et al.
Published: (2024)

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

Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning
by: Shi, Yujun, et al.
Published: (2021)

Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion
by: Huang, Linlan, et al.
Published: (2024)

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning
by: Lee, Juntae, 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)

Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning
by: Jiang, Kai, et al.
Published: (2025)

Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning
by: Liang, Jinglin, et al.
Published: (2024)

Continuous Unsupervised Domain Adaptation Using Stabilized Representations and Experience Replay
by: Rostami, Mohammad
Published: (2024)

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

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning
by: Zhou, Da-Wei, et al.
Published: (2024)

CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning
by: Javadi, Amirhosein, et al.
Published: (2026)

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
by: Sun, Hai-Long, et al.
Published: (2024)

Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning
by: Chen, Wei, et al.
Published: (2024)