Time Series papers, 2023–2026

Key findings

• Time Series went from 272 papers in 2023 to 876 in 2026, roughly 3.2x in three years.
• NeurIPS publishes the most Time Series work: 757 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 6 in 2023 to 85 in 2026.
• Among the 5 topics under Graph and Structured Data, it ranks #1 by 2026 paper count; the fastest grower in the group, Molecular Modeling, is up 2.7x versus 3.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Batched Hartigan's $k$-Means Clustering
• ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026Activation Matters Test-time Activated Negative Labels for OOD Detection with
• NeurIPS 2025Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
• ICML 2025$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
• ICLR 2025A deep inverse-mapping model for a flapping robotic wing
• CVPR 2025Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and Harmonization
• NeurIPS 2024A Continuous-time Stochastic Gradient Descent Method for Continuous Data
• ICML 2024$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
• ICLR 2024ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
• CVPR 2024Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation
• NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
• ICML 2023Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
• ICLR 2023A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
• CVPR 2023ActMAD: Activation Matching To Align Distributions for Test-Time-Training
• NeurIPS 2026A Locally Tokenized Generative Model for Robust Time-Series Watermarking
• ICML 2026ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
• ICLR 2026A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems
• CVPR 2026Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis

All Time Series papers

506 papers, page 5 of 11

201. ICLR 2026Topological Anomaly Quantification for Semi-supervised Graph Anomaly Detection
202. ICLR 2026Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
203. ICLR 2026Towards Multimodal Time Series Anomaly Detection with Semantic Alignment and Condensed Interaction
204. ICLR 2026Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependency, Asynchrony, and Missingness
205. ICLR 2026Transformers Don’t Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and Implications for Mechanistic Interpretability
206. ICLR 2026TreeGrad-Ranker: Feature Ranking via $O(L)$-Time Gradients for Decision Trees
207. ICLR 2026TrimR: Verifier-based Training-Free Thinking Trimming for Efficient Test-Time Scaling
208. ICLR 2026TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis
209. ICLR 2026Understanding the Implicit Biases of Design Choices for Time Series Foundation Models
210. ICLR 2026UNDERSTANDING TRANSFORMERS FOR TIME SEIRES FORECASTING: A CASE STUDY ON MOIRAI
211. ICLR 2026Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility
212. ICLR 2026UniCA: Unified Covariate Adaptation for Time Series Foundation Model
213. ICLR 2026Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecasting
214. ICLR 2026Unmasking Backdoors: An Explainable Defense via Gradient-Attention Anomaly Scoring for Pre-trained Language Models
215. ICLR 2026Weight-Space Linear Recurrent Neural Networks
216. ICLR 2026When and Where to Reset Matters for Long-Term Test-Time Adaptation
217. ICLR 2026When Foundation Models are One-Liners: Limitations and Future Directions for Time Series Anomaly Detection
218. ICLR 2026When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency
219. ICLR 2026xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
220. ICLR 2026Zero-shot Forecasting by Simulation Alone
221. ICLR 2025A deep inverse-mapping model for a flapping robotic wing
222. ICLR 2025A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics
223. ICLR 2025Adaptive Retention & Correction: Test-Time Training for Continual Learning
224. ICLR 2025Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation
225. ICLR 2025Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
226. ICLR 2025Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
227. ICLR 2025AnoLLM: Large Language Models for Tabular Anomaly Detection
228. ICLR 2025AutoUAD: Hyper-parameter Optimization for Unsupervised Anomaly Detection
229. ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
230. ICLR 2025Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
231. ICLR 2025Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
232. ICLR 2025Can LLMs Understand Time Series Anomalies?
233. ICLR 2025CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching
234. ICLR 2025CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series
235. ICLR 2025Classic but Everlasting: Traditional Gradient-Based Algorithms Converge Fast Even in Time-Varying Multi-Player Games
236. ICLR 2025COME: Test-time Adaption by Conservatively Minimizing Entropy
237. ICLR 2025Compositional simulation-based inference for time series
238. ICLR 2025Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
239. ICLR 2025CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution
240. ICLR 2025Context Steering: Controllable Personalization at Inference Time
241. ICLR 2025Context-Alignment: Activating and Enhancing LLMs Capabilities in Time Series
242. ICLR 2025Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt
243. ICLR 2025Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements
244. ICLR 2025Controlling Space and Time with Diffusion Models
245. ICLR 2025Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
246. ICLR 2025Differentially Private Federated Learning with Time-Adaptive Privacy Spending
247. ICLR 2025DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector
248. ICLR 2025Diffusion Transformers for Tabular Data Time Series Generation
249. ICLR 2025Diffusion-based Decoupled Deterministic and Uncertain Framework for Probabilistic Multivariate Time Series Forecasting
250. ICLR 2025DRL: Decomposed Representation Learning for Tabular Anomaly Detection

FAQ

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

2,157 in total: 272 in 2023, 424 in 2024, 585 in 2025, 876 in 2026.

How many Time Series papers are at NeurIPS 2026?

NeurIPS 2026 has 298 Time Series papers, versus 221 the year before.

How many Time Series papers are at ICLR 2026?

ICLR 2026 has 220 Time Series papers, versus 131 the year before.

How many Time Series papers are at ICML 2026?

ICML 2026 has 264 Time Series papers, versus 159 the year before.

How many Time Series papers are at CVPR 2026?

CVPR 2026 has 94 Time Series papers, versus 74 the year before.

Which conference publishes the most Time Series papers?

NeurIPS, with 757 papers from 2023 to 2026.