"catastrophic forgetting" Papers
127 papers found • Page 1 of 3
Conference
AdaDARE-gamma: Balancing Stability and Plasticity in Multi-modal LLMs through Efficient Adaptation
Jingyi Xie, Jintao Yang, Zhunchen Luo et al.
ADAPT: Attentive Self-Distillation and Dual-Decoder Prediction Fusion for Continual Panoptic Segmentation
Ze Yang, Shichao Dong, Ruibo Li et al.
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning
Takuma Fukuda, Hiroshi Kera, Kazuhiko Kawamoto
Adaptive Prototype Replay for Class Incremental Semantic Segmentation
Guilin Zhu, Dongyue Wu, Changxin Gao et al.
Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging
Xianrui Li, Yufei Cui, Jun Li et al.
AnaCP: Toward Upper-Bound Continual Learning via Analytic Contrastive Projection
Saleh Momeni, Changnan Xiao, Bing Liu
Buffer layers for Test-Time Adaptation
Hyeongyu Kim, GeonHui Han, Dosik Hwang
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering
Tianyu Huai, Jie Zhou, Xingjiao Wu et al.
CMT: A Memory Compression Method for Continual Knowledge Learning of Large Language Models
Dongfang Li, Zetian Sun, Xinshuo Hu et al.
CODE-CL: Conceptor-Based Gradient Projection for Deep Continual Learning
Marco P. Apolinario, Sakshi Choudhary, Kaushik Roy
Continual Knowledge Adaptation for Reinforcement Learning
Jinwu Hu, ZiHao Lian, Zhiquan Wen et al.
Continual Personalization for Diffusion Models
Yu-Chien Liao, Jr-Jen Chen, Chi-Pin Huang et al.
Continuous Subspace Optimization for Continual Learning
Quan Cheng, Yuanyu Wan, Lingyu Wu et al.
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun
Coreset Selection via Reducible Loss in Continual Learning
Ruilin Tong, Yuhang Liu, Javen Qinfeng Shi et al.
DASK: Distribution Rehearsing via Adaptive Style Kernel Learning for Exemplar-Free Lifelong Person Re-Identification
Kunlun Xu, Chenghao Jiang, Peixi Xiong et al.
DCA: Dividing and Conquering Amnesia in Incremental Object Detection
Aoting Zhang, Dongbao Yang, Chang Liu et al.
Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning
Danni Yang, Zhikang Chen, Sen Cui et al.
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning
Yilun Li, Miaomiao Cheng, Xu Han et al.
DocThinker: Explainable Multimodal Large Language Models with Rule-based Reinforcement Learning for Document Understanding
Wenwen Yu, Zhibo Yang, Yuliang Liu et al.
Do Your Best and Get Enough Rest for Continual Learning
Hankyul Kang, Gregor Seifer, Donghyun Lee et al.
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic
Munish Monga, Vishal Chudasama, Pankaj Wasnik et al.
Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
Zhiyuan Zhou, Andy Peng, Qiyang Li et al.
ESSENTIAL: Episodic and Semantic Memory Integration for Video Class-Incremental Learning
Jongseo Lee, Kyungho Bae, Kyle Min et al.
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
Wei Chen, Yuxuan Liang
Federated Continual Instruction Tuning
Haiyang Guo, Fanhu Zeng, Fei Zhu et al.
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
Few-Shot, No Problem: Descriptive Continual Relation Extraction
Nguyen Xuan Thanh, Anh Duc Le, Quyen Tran et al.
Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
Hao Yu, Xin Yang, Le Zhang et al.
Hierarchical Visual Prompt Learning for Continual Video Instance Segmentation
Jiahua Dong, Hui Yin, Wenqi Liang et al.
High-dimension Prototype is a Better Incremental Object Detection Learner
Yanjie Wang, Liqun Chen, Tianming Zhao et al.
Hippocampal-like Sequential Editing for Continual Knowledge Updates in Large Language Models
Quntian Fang, Zhen Huang, Zhiliang Tian et al.
HMVLM:Human Motion-Vision-Language Model via MoE LoRA
Lei Hu, Yongjing Ye, Shihong Xia
iManip: Skill-Incremental Learning for Robotic Manipulation
Zexin Zheng, Jia-Feng Cai, Xiao-Ming Wu et al.
Joint Diffusion Models in Continual Learning
Paweł Skierś, Kamil Deja
Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning
Xusheng Cao, Haori Lu, Linlan Huang et al.
LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging
Ke Wang, Nikos Dimitriadis, Alessandro Favero et al.
Looking Beyond the Known: Towards a Data Discovery Guided Open-World Object Detection
Anay Majee, Amitesh Gangrade, Rishabh Iyer
LoRA Learns Less and Forgets Less
Jonathan Frankle, Jose Javier Gonzalez Ortiz, Cody Blakeney et al.
LoRA Subtraction for Drift-Resistant Space in Exemplar-Free Continual Learning
Xuan Liu, Xiaobin Chang
MaintaAvatar: A Maintainable Avatar Based on Neural Radiance Fields by Continual Learning
Shengbo Gu, Yu-Kun Qiu, Yu-Ming Tang et al.
Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning
Wei Chen, Yi Zhou
MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification
Jimin Park, AHyun Ji, Minji Park et al.
Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models
Jiaqi Cao, Jiarui Wang, Rubin Wei et al.
Memory-Integrated Reconfigurable Adapters: A Unified Framework for Settings with Multiple Tasks
Susmit Agrawal, Krishn Vishwas Kher, Saksham Mittal et al.
MINGLE: Mixture of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Merging
Zihuan Qiu, Yi Xu, Chiyuan He et al.
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao et al.
One-for-More: Continual Diffusion Model for Anomaly Detection
Xiaofan Li, Xin Tan, Zhuo Chen et al.
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf et al.
Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
Guannan Lai, Yujie Li, Xiangkun Wang et al.