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

381 papers, page 6 of 8

251. CVPR 2024Semantically-Shifted Incremental Adapter-Tuning is A Continual ViTransformer
252. CVPR 2024Towards Backward-Compatible Continual Learning of Image Compression
253. CVPR 2024Traceable Federated Continual Learning
254. ICLR 2024A Probabilistic Framework for Modular Continual Learning
255. ICLR 2024Accurate Forgetting for Heterogeneous Federated Continual Learning
256. ICLR 2024Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning
257. ICLR 2024Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline
258. ICLR 2024Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
259. ICLR 2024Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation
260. ICLR 2024Efficient Continual Finite-Sum Minimization
261. ICLR 2024Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning
262. ICLR 2024Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks
263. ICLR 2024Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction
264. ICLR 2024Prompt Gradient Projection for Continual Learning
265. ICLR 2024Scalable Language Model with Generalized Continual Learning
266. ICLR 2024The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model
267. ICLR 2024TiC-CLIP: Continual Training of CLIP Models
268. ICML 2024An Effective Dynamic Gradient Calibration Method for Continual Learning
269. ICML 2024COPAL: Continual Pruning in Large Language Generative Models
270. ICML 2024Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet
271. ICML 2024Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
272. ICML 2024Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning
273. ICML 2024Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization
274. ICML 2024On the Diminishing Returns of Width for Continual Learning
275. ICML 2024One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
276. ICML 2024Provable Contrastive Continual Learning
277. ICML 2024Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
278. ICML 2024Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
279. ICML 2024Self-Composing Policies for Scalable Continual Reinforcement Learning
280. ICML 2024Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
281. ICML 2024Understanding Forgetting in Continual Learning with Linear Regression
282. NeurIPS 2024A Topology-aware Graph Coarsening Framework for Continual Graph Learning
283. NeurIPS 2024CoIN: A Benchmark of Continual Instruction Tuning for Multimodel Large Language Models
284. NeurIPS 2024Continual Learning in the Frequency Domain
285. NeurIPS 2024Continual Learning with Global Alignment
286. NeurIPS 2024Continual learning with the neural tangent ensemble
287. NeurIPS 2024Disentangling and mitigating the impact of task similarity for continual learning
288. NeurIPS 2024Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning
289. NeurIPS 2024GACL: Exemplar-Free Generalized Analytic Continual Learning
290. NeurIPS 2024Label Delay in Online Continual Learning
291. NeurIPS 2024Learn more, but bother less: parameter efficient continual learning
292. NeurIPS 2024Learning Successor Features the Simple Way
293. NeurIPS 2024Leveraging Catastrophic Forgetting to Develop Safe Diffusion Models against Malicious Finetuning
294. NeurIPS 2024Make Continual Learning Stronger via C-Flat
295. NeurIPS 2024Mixture of Experts Meets Prompt-Based Continual Learning
296. NeurIPS 2024Model Sensitivity Aware Continual Learning
297. NeurIPS 2024Parseval Regularization for Continual Reinforcement Learning
298. NeurIPS 2024Persistence Homology Distillation for Semi-supervised Continual Learning
299. NeurIPS 2024Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training
300. NeurIPS 2024Saliency-driven Experience Replay for Continual Learning

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.