Continual Learning

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Period ending 2026-09-21

14 new papers

A weekly snapshot of new work published in Continual Learning.

Period ending 2026-09-14

11 new papers

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Period ending 2026-09-07

8 new papers

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Continual Learning Methods

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229 papersExplore

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Efficient Continual Learning

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Catastrophic Forgetting

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151 papersExplore

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Forgetting

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Plasticity

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81 papersExplore

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Domain Incremental Learning

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62 papersExplore

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Retention

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51 papersExplore

621 papers

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HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning
May 7, 2026Yu Feng, Zhen Tian, Haoran Luo +8Domain Incremental Learning Domain Adaptation
Priming, Path-dependence, and Plasticity: Understanding the molding of user-LLM interaction and its implications from (many) chat logs in the wild
May 7, 2026Shengqi Zhu, Jeffrey M. Rzeszotarski, David MimnoChatbots Priming
MaMi-HOI: Harmonizing Global Kinematics and Local Geometry for Human-Object Interaction Generation
May 7, 2026Hao Wang, Shiqi Wang, Qi LiuArticulated Objects Pose-Guided Kinematic Reasoning
CoMemNet: Contrastive Sampling with Memory Replay Network for Continual Traffic Prediction
May 7, 2026Mei Wu, Wenchao Weng, Wenxin Su +2Accurate Traffic Forecasting Temporal Graph Neural Networks
CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning
May 7, 2026Md Anwar Hossen, Fatema Siddika, Juan Pablo Munoz +2Catastrophic Forgetting Large Language Model Adaptation
From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms
May 7, 2026Jinghao Luo, Yuchen Tian, Chuxue Cao +6Agent Memory Experience
Shortcut Solutions Learned by Transformers Impair Continual Compositional Reasoning
May 6, 2026William T. Redman, Erik C. Johnson, Brian RobinsonTransformer Architectures Efficient Continual Learning
Balancing Stability and Plasticity in Sequentially Trained Early-Exiting Neural Networks
May 6, 2026Alaa Zniber, Ouassim Karrakchou, Mounir GhoghoPlasticity Early Stopping
Attribution-Guided Continual Learning for Large Language Models
May 6, 2026Yazheng Liu, Yuxuan Wan, Rui Xu +3Large Language Model Fine-Tuning Catastrophic Forgetting
Skill Neologisms: Towards Skill-based Continual Learning
May 6, 2026Antonin Berthon, Nicolas Astorga, Mihaela van der SchaarUnsupervised Skill Discovery Efficient Continual Learning
Replay-Based Continual Learning for Physics-Informed Neural Operators
May 6, 2026Yizheng Wang, Mohammad Sadegh Eshaghi, Xiaoying Zhuang +2Neural Operators Efficient Continual Learning
Guidelines for Designing AI Technologies to Support Adult Learning
May 6, 2026Jennifer M. Reddig, Glen R. Smith, Sanaz Ahmadzadeh Siyahrood +16Education Classrooms
Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional Control
May 6, 2026Xinyu Wang, Changzhi Sun, Yuanbin Wu +1Supervised Fine-Tuning Finetuning
FLUID: Continuous-Time Hyperconnected Sparse Transformer for Sink-Free Learning
May 6, 2026Waleed Razzaq, Yun-Bo ZhaoTransformer Architectures Efficient Continual Learning
Memory as a Markov Matrix: Sample Efficient Knowledge Expansion via Token-to-Dictionary Mapping
May 5, 2026Kaustubh Pethkar, Ziyang Xiong, Zuofeng Shang +1Large Language Model Memory Autoregressive Language Models
Memory-Efficient Continual Learning with CLIP Models
May 5, 2026Ryan King, Gang Li, Bobak Mortazavi +1Domain Incremental Learning Frozen Contrastive Language-Image Pre-Training Visual Encoder
ScrapMem: A Bio-inspired Framework for On-device Personalized Agent Memory via Optical Forgetting
May 5, 2026Jiale Chang, Yuxiang RenAgent Memory Catastrophic Forgetting
Before Forgetting, Learn to Remember: Revisiting Foundational Learning Failures in LVLM Unlearning Benchmarks
May 5, 2026JuneHyoung Kwon, MiHyeon Kim, Eunju Lee +3Large Vision Language Models Forgetting
CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment
May 5, 2026Siyuan Guo, Yali Du, Hechang Chen +2Large Language Model Agents Efficient Continual Learning
Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models
May 5, 2026JuneHyoung Kwon, JungMin Yun, YoungBin KimLarge Vision Language Models Unlearning Aims
Dynamic Distillation and Gradient Consistency for Robust Long-Tailed Incremental Learning
May 5, 2026Taigo Sakai, Kazuhiro HottaDomain Incremental Learning Continual Learning Methods
Sparse Memory Finetuning as a Low-Forgetting Alternative to LoRA and Full Finetuning
May 4, 2026Prakhar Gupta, Garv Shah, Satyam Goyal +1Large Language Model Memory Forgetting
Adaptive Data Compression and Reconstruction for Memory-Bounded EEG Continual Learning
May 4, 2026Chengcheng XieElectroencephalography Spatial Super-Resolution Efficient Continual Learning
Automated In-the-Wild Data Collection for Continual AI Generated Image Detection
May 4, 2026Thanasis Pantsios, Dimitrios Karageorgiou, Christos Koutlis +3Ai-Generated Image Detection Generative Artificial Intelligence
MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC
May 4, 2026Joern HentschPlasticity Synaptic Plasticity
DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning
May 4, 2026Abdullah Ahmad Khan, Ferdous SohelMachine Unlearning Catastrophic Forgetting
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
May 4, 2026Ishaan Watts, Catherine Li, Sachin Goyal +2Catastrophic Forgetting LLM Post-Training Methods
HERCULES: Hardware-Efficient, Robust, Continual Learning Neural Architecture Search
May 3, 2026Matteo Gambella, Fabrizio Pittorino, Manuel RoveriNeural Architecture Search Artificial Intelligence Infrastructure
Sequential Learning and Catastrophic Forgetting in Differentiable Resistor Networks
May 2, 2026Maniru IbrahimCatastrophic Forgetting Forgetting
Autonomous Drift Learning in Data Streams: A Unified Perspective
May 2, 2026Xiaoyu Yang, En Yu, Jie LuNon-Stationarity Continual Learning Methods
Forager: a lightweight testbed for continual learning with partial observability in RL
May 1, 2026Steven Tang, Xinze Xiong, Anna Hakhverdyan +7Efficient Continual Learning Partial Observability
Continual Learning of Feedback-based Molecular Communication
May 1, 2026Siddhant Setia, Junichi Suzuki, Tadashi NakanoEfficient Continual Learning Continual Learning Methods
EASE: Federated Multimodal Unlearning via Entanglement-Aware Anchor Closure
May 1, 2026Zihao Ding, Beining Wu, Jun HuangLarge Language Model Unlearning Cross-Modal Learning
Unlearning What Matters: Token-Level Attribution for Precise Language Model Unlearning
May 1, 2026Jiawei Wu, Doudou ZhouToken-Level Uncertainty Catastrophic Forgetting
When Does Structure Matter in Continual Learning? Dimensionality Controls When Modularity Shapes Representational Geometry
Apr 30, 2026Kathrin Korte, Joachim Winter Pedersen, Eleni Nisioti +1Continual Learning Methods Plasticity
Learning to Forget: Continual Learning with Adaptive Weight Decay
Apr 29, 2026Aditya A. Ramesh, Alex Lewandowski, Jürgen SchmidhuberLearning Rates Continual Learning Methods
NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning
Apr 29, 2026Karthik Charan Raghunathan, Christian Metzner, Laura Kriener +1Efficient Continual Learning Continual Learning Methods
NeuroPlastic: A Plasticity-Modulated Optimizer for Biologically Inspired Learning Dynamics
Apr 29, 2026Douglas Jiang, Yuechen Wang, Jiayi Wang +3Neural Network Optimization Plasticity
When Continual Learning Moves to Memory: A Study of Experience Reuse in LLM Agents
Apr 29, 2026Qisheng Hu, Quanyu Long, Wenya WangContinual Learning Methods Large Language Model Agents
TSN-Affinity: Similarity-Driven Parameter Reuse for Continual Offline Reinforcement Learning
Apr 28, 2026Dominik Żurek, Kamil Faber, Marcin Pietron +2Offline Reinforcement Learning Efficient Continual Learning
CoRE: Concept-Reasoning Expansion for Continual Brain Lesion Segmentation
Apr 28, 2026Qianqian Chen, Anglin Liu, Jingyang Zhang +1Brain Tumor Segmentation Efficient Continual Learning
Cortex-Inspired Continual Learning: Unsupervised Instantiation and Recovery of Functional Task Networks
Apr 27, 2026Kevin McKee, Thomas Hazy, Yicong Zheng +2Efficient Continual Learning Deep Network
Continual Calibration: Coverage Can Collapse Before Accuracy in Lifelong LLM Fine-Tuning
Apr 27, 2026Ibne Farabi Shihab, Sanjeda Akter, Anuj SharmaMulticalibration and Calibration Continual Learning Methods
OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving
Apr 26, 2026Chenyi Li, Yanchen Nie, Zhenyu Ming +3Theorem Olympiad-Level Problem
AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
Apr 25, 2026Xudong Jiang, Mingshan Loo, Hanchen Yang +5Frequency Domain Mamba
Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair
Apr 24, 2026Yuelin Hu, Zhenbo Yu, Zhengxue Cheng +2Adam Efficient Continual Learning
Do Not Imitate, Reinforce: Iterative Classification via Belief Refinement
Apr 23, 2026Mahdi Kallel, Johannes Tölle, Ahmed Hendawy +1Domain Incremental Learning Object Classification
PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning
Apr 23, 2026Xiaoyi Chen, Haoyuan Wang, Siyuan Tang +4Exact Unlearning Efficient Privacy Loss
Temporal Taskification in Streaming Continual Learning: A Source of Evaluation Instability
Apr 23, 2026Nicolae Filat, Ahmed Hussain, Konstantinos Kalogiannis +1Efficient Continual Learning Sequential
Fine-Tuning Regimes Define Distinct Continual Learning Problems
Apr 23, 2026Paul-Tiberiu Iordache, Elena BurceanuEfficient Continual Learning Continual Fine-Tuning
To See the Unseen: on the Generalization Ability of Transformers in Symbolic Reasoning
Apr 23, 2026Nevena Lazić, Liam Fowl, András György +1Transformer Encoder Transformer Architectures
ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing
Apr 23, 2026Jebacyril Arockiaraj, Dhruv Parikh, Viktor PrasannaEfficient Continual Learning Real-Time Inference
Lifecycle-Aware Federated Continual Learning in Mobile Autonomous Systems
Apr 22, 2026Beining Wu, Jun HuangEfficient Continual Learning Continual Learning Methods
COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling
Apr 22, 2026Noah FlynnMultilingual Language Models Large Language Model Adaptation
LAF-Based Evaluation and UTTL-Based Learning Strategies with MIATTs
Apr 22, 2026Yongquan YangCross-Entropy Losses Continual Learning Methods
SCM: Sleep-Consolidated Memory with Algorithmic Forgetting for Large Language Models
Apr 22, 2026Saish Sachin ShindeLarge Language Model Memory Catastrophic Forgetting
Ask Only When Needed: Proactive Retrieval from Memory and Skills for Experience-Driven Lifelong Agents
Apr 22, 2026Yuxuan Cai, Wei Li, Jie Zhou +4Agentic Reinforcement-Learning Framework Agent Memory
Toward Cross-Lingual Quality Classifiers for Multilingual Pretraining Data Selection
Apr 22, 2026Yassine Turki, Vinko Sabolčec, Bettina Messmer +1Multilingual Language Models Cross-Lingual Consistency
FSFM: A Biologically-Inspired Framework for Selective Forgetting of Agent Memory
Apr 22, 2026Yingjie Gu, Wenjian Xiong, Liqiang Wang +7Agent Memory Catastrophic Forgetting
Absorber LLM: Harnessing Causal Synchronization for Test-Time Training
Apr 22, 2026Zhixin Zhang, Shabo Zhang, Chengcan Wu +2Efficient Long-Context Inference Large Language

May 7, 2026 · cs.AIJ/K move · Enter open · S save

HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning

Yu Feng, Zhen Tian, Haoran Luo, Xie Yu+7

China Mobile Research Institute, China · Beijing University of Posts and Telecommunications, China · Nanyang Technological University, Singapore · Beihang University, China

Domain Incremental Learning is a critical scenario that requires models to continuously adapt to new data domains without retraining. However, domain shifts often cause severe performance degradation. To address this, we propose Hybrid Energy-Distance Prompt, a domain-incremental framework inspired by Helmholtz free energy. HEDP introduces an energy regularization loss to enhance the separability of domain representations and a hybrid energy-distance weighted mechanism that fuses energy-based and distance-based cues to improve domain selection and generalization. Experiments on multiple benchmarks, including CORe50, show that HEDP achieves superior performance on unseen domains with a 2.57% accuracy gain, effectively mitigating catastrophic forgetting and enhancing open-world adaptability. Our code is \href{https://github.com/dannis97500/HEDP/}{available here}.

Domain Incremental Learning Domain Adaptation Catastrophic Forgetting Regularization Techniques

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