Continual Learning papers, 2023–2026

Key findings

• Continual Learning went from 77 papers in 2023 to 131 in 2026, roughly 1.7x in three years.
• NeurIPS publishes the most Continual Learning work: 121 papers from 2023 to 2026, 32% of the four-venue total.
• The fastest-growing overlap is with Low-Rank Adaptation: papers tagged with both rose from 1 in 2023 to 16 in 2026.
• Among the 5 topics under Meta-Learning and Transfer, it ranks #5 by 2026 paper count; the fastest grower in the group, Foundation Model Adaptation, is up 3.8x versus 1.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Bayes-pFCL:Bayesian Personalized Federated Continual Learning
• ICML 2026Beyond Buffer Limits: Energy-Based Data Reassembly for Continual Learning
• ICLR 2026FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
• CVPR 2026A Faster Path to Continual Learning
• NeurIPS 2025AnaCP: Toward Upper-Bound Continual Learning via Analytic Contrastive Projection
• ICML 2025BECAME: Bayesian Continual Learning with Adaptive Model Merging
• ICLR 2025Active Learning for Continual Learning: Keeping the Past Alive in the Present
• CVPR 2025AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering
• NeurIPS 2024CoIN: A Benchmark of Continual Instruction Tuning for Multimodel Large Language Models
• ICML 2024An Effective Dynamic Gradient Calibration Method for Continual Learning
• ICLR 2024A Probabilistic Framework for Modular Continual Learning
• CVPR 2024Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay
• NeurIPS 2023Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
• ICML 2023Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation
• ICLR 2023Artificial Neuronal Ensembles with Learned Context Dependent Gating
• CVPR 2023Achieving a Better Stability-Plasticity Trade-Off via Auxiliary Networks in Continual Learning
• NeurIPS 2026Beyond Exemplar Selection: Value-Aware Memory Allocation in Replay-Based Continual Learning
• ICML 2026BTSP-CAM: A Brain-Inspired Geometric Memory for Class-Incremental Learning
• ICLR 2026IDER: IDEMPOTENT EXPERIENCE REPLAY FOR RELIABLE CONTINUAL LEARNING
• CVPR 2026AdaPrior Bayesian-Inspired Adaptive Prior Correction for Long-Tailed Continual Learning

All Continual Learning papers

77 papers, page 2 of 2

51. NeurIPS 2023A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks
52. NeurIPS 2023A Definition of Continual Reinforcement Learning
53. NeurIPS 2023Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
54. NeurIPS 2023An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
55. NeurIPS 2023CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation
56. NeurIPS 2023CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence
57. NeurIPS 2023Continual Learning for Instruction Following from Realtime Feedback
58. NeurIPS 2023COOM: A Game Benchmark for Continual Reinforcement Learning
59. NeurIPS 2023Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework
60. NeurIPS 2023Evolving Standardization for Continual Domain Generalization over Temporal Drift
61. NeurIPS 2023Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments
62. NeurIPS 2023FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
63. NeurIPS 2023Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
64. NeurIPS 2023Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality
65. NeurIPS 2023Improving Language Plasticity via Pretraining with Active Forgetting
66. NeurIPS 2023Loss Decoupling for Task-Agnostic Continual Learning
67. NeurIPS 2023Nearly Optimal Bounds for Cyclic Forgetting
68. NeurIPS 2023NPCL: Neural Processes for Uncertainty-Aware Continual Learning
69. NeurIPS 2023On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm
70. NeurIPS 2023Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation
71. NeurIPS 2023Prompt-augmented Temporal Point Process for Streaming Event Sequence
72. NeurIPS 2023RanPAC: Random Projections and Pre-trained Models for Continual Learning
73. NeurIPS 2023RDumb: A simple approach that questions our progress in continual test-time adaptation
74. NeurIPS 2023Rewiring Neurons in Non-Stationary Environments
75. NeurIPS 2023Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation
76. NeurIPS 2023The Tunnel Effect: Building Data Representations in Deep Neural Networks
77. NeurIPS 2023TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion

FAQ

How many Continual Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

381 in total: 77 in 2023, 69 in 2024, 104 in 2025, 131 in 2026.

How many Continual Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 39 Continual Learning papers, versus 32 the year before.

How many Continual Learning papers are at ICLR 2026?

ICLR 2026 has 28 Continual Learning papers, versus 23 the year before.

How many Continual Learning papers are at ICML 2026?

ICML 2026 has 42 Continual Learning papers, versus 29 the year before.

How many Continual Learning papers are at CVPR 2026?

CVPR 2026 has 22 Continual Learning papers, versus 20 the year before.

Which conference publishes the most Continual Learning papers?

NeurIPS, with 121 papers from 2023 to 2026.