Key papers

• Dynamic Trend Fusion Module for Traffic Flow Prediction (2025)
  Jing Chen et al.
  10.70
• Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting (2025)
  Siru Zhong et al.
  10.43
• FinBERT-BiLSTM: A Deep Learning Model for Predicting Volatile Cryptocurrency Market Prices Using Market Sentiment Dynamics (2024)
  Mabsur Fatin Bin Hossain et al.
  8.75
• ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables (2025)
  Sebastian Pineda Arango et al.
  7.84
• FTS: A Framework to Find a Faithful TimeSieve (2024)
  Songning Lai et al.
  7.27
• FinCast: A Foundation Model for Financial Time-Series Forecasting (2025)
  Zhuohang Zhu et al.
  7.06
• Physics-informed deep learning for infectious disease forecasting (2025)
  Ying Qian et al.
  6.67
• Panda: A pretrained forecast model for chaotic dynamics (2025)
  Jeffrey Lai et al.
  6.47
• FlowState: Sampling Rate Invariant Time Series Forecasting (2025)
  Lars Graf et al.
  6.39
• Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts (2024)
  Xiaoming Shi et al.
  6.36
• Seasonal Forecasting of Pan-Arctic Sea Ice with State Space Model (2025)
  Wei Wang et al.
  6.23
• Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models (2023)
  Alejandro Lopez-Lira and Yuehua Tang
  6.12
• EnergyPatchTST: Multi-scale Time Series Transformers with Uncertainty Estimation for Energy Forecasting (2025)
  Wei Li et al.
  6.09
• Avocado Price Prediction Using a Hybrid Deep Learning Model: TCN-MLP-Attention Architecture (2025)
  Linwei Zhang et al.
  5.96
• Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Tasks (2024)
  Zijian Zhang et al.
  5.91
• Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather (2025)
  Philine L. Bommer et al.
  5.90
• Transformer Model for Alzheimer's Disease Progression Prediction Using Longitudinal Visit Sequences (2025)
  Mahdi Moghaddami et al.
  5.76
• Adapformer: Adaptive Channel Management for Multivariate Time Series Forecasting (2025)
  Yuchen Luo et al.
  5.63
• Cross-Modal Temporal Fusion for Financial Market Forecasting (2025)
  Yunhua Pei and John Cartlidge and Anandadeep Mandal and Daniel Gold and Enrique Marcilio and Riccardo Mazzon
  5.59
• Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting (2024)
  Chu Myaet Thwal et al.
  5.51
• Using Pre-trained LLMs for Multivariate Time Series Forecasting (2025)
  Malcolm L. Wolff et al.
  5.43
• TempoGPT: Enhancing Time Series Reasoning via Quantizing Embedding (2025)
  Haochuan Zhang et al.
  5.43
• Timer-XL: Long-Context Transformers for Unified Time Series Forecasting (2024)
  Yong Liu et al.
  5.02
• A novel forecasting framework combining virtual samples and enhanced Transformer models for tourism demand forecasting (2025)
  Tingting Diao et al.
  4.76
• CITRAS: Covariate-Informed Transformer for Time Series Forecasting (2025)
  Yosuke Yamaguchi et al.
  4.76
• Self-attentive Transformer for Fast and Accurate Postprocessing of Temperature and Wind Speed Forecasts (2024)
  Aaron Van Poecke et al.
  4.71
• Selective Learning for Deep Time Series Forecasting (2025)
  Yisong Fu et al.
  4.64
• T3Time: Tri-Modal Time Series Forecasting via Adaptive Multi-Head Alignment and Residual Fusion (2025)
  Abdul Monaf Chowdhury et al.
  4.53
• Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting (2025)
  Timoth\'ee Hornek Amir Sartipi and Igor Tchappi and Gilbert Fridgen
  4.42
• A Comparative Study of Transformer-Based Models for Multi-Horizon Blood Glucose Prediction (2025)
  Meryem Altin Karagoz et al.
  4.36
• Quantize the Target, Quantize the Drafter: Efficient Inference with Qwen3.5-4B (2026)
  Jaeyeon Kim et al.
  4.33
• LLM-Guided Measurement Credibility Correction for Trustworthy Industrial Process Inference (2026)
  Youcheng Zong et al.
  4.33
• GRATE: Temporal Extensions for Inductive KG Foundation Models via Gated Rotary Attention (2026)
  Jiaxin Pan et al.
  4.33
• Can Agentic Trading Systems Pay for Their Own Intelligence? (2026)
  Qiqi Duan et al.
  4.33
• SPARK: Susceptibility-Guided Profiling and Steering of Latent Reasoning States in Large Language Models (2026)
  Dongxu Zhang et al.
  4.33
• Laguerre Geometry for Interpreting Large Language Models (2026)
  Chunwei Ma et al.
  4.33
• WattCouncil: Context-Aware Household Energy Scenario Generation With Governed LLMs (2026)
  Mohannad Takrouri et al.
  4.33
• Incremental Transformer for Surrogate-Based Inverse Design of Geopolymer Mixtures (2026)
  Giansalvo Cirrincione et al.
  4.33
• Edge Physical AI Deployment of Vision Transformers on Heterogeneous Edge GPU Targeting Autonomous Vehicles (2026)
  Ashiyana Abdul Majeed et al.
  4.33
• From Checker to Forecaster: Code-Owned Evaluation of Model-Generated Strategic Routes Under Delayed Ground Truth (2026)
  Aleh Manchuliantsau
  4.33
• Agentic Routing: The Harness-Native Data Flywheel (2026)
  Xinchen Liu et al.
  4.33
• Robustness of Deep Learning Models for PV Power Forecasting under NWP Forecast Errors: A Spatiotemporal and Physically Interpretable Analysis (2026)
  Dandan Chen et al.
  4.33
• MMformer with Adaptive Transferable Attention: Advancing Multivariate Time Series Forecasting for Environmental Applications (2025)
  Ning Xin et al.
  4.30
• FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance (2026)
  Jiaze Sun et al.
  4.27
• PatchSTG: Scalable Spatiotemporal Graph Transformers for Traffic Forecasting on Irregular Sensor Networks (2026)
  Jichao Li et al.
  4.27
• ASTEROID: A Spatiotemporal Information Transformer for Forecasting Multi-Step Time Series of Molecular Dynamics (2026)
  Kexin Wu et al.
  4.27
• Delta-Based Target Reformulation for Short-Term Electricity Load Forecasting Using LSTM and Transformer Models (2026)
  Vansh Bansal
  4.27
• ConTex: Reformulating Counterfactual Generation For Time Series Forecasting (2026)
  Jan Voets et al.
  4.27
• TelcoAgent: A Scalable 5G Multi-KPM Forecasting With 3GPP-Grounded Explainability (2026)
  Geon Kim et al.
  4.27
• World Machine: Towards Generative World Modeling for Time-Series (2026)
  Elton Cardoso do Nascimento et al.
  4.22
• ADMFormer: An Adaptive-Decomposition Transformer with Time-Varying Masked Spatial Attention for Traffic Forecasting (2026)
  Ruiwen Gu et al.
  4.22
• BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting (2026)
  Ruifeng Tan et al.
  4.22
• Enhanced Photovoltaic Power Forecasting: An iTransformer and LSTM-Based Model Integrating Temporal and Covariate Interactions (2024)
  Guang Wu et al.
  4.19
• CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements (2025)
  Yang Zhang et al.
  4.19
• LLM-driven hybrid architecture for multi-variate and multi-horizon forecasting of consumption patterns using graphs, recurrent units, and transformers (2026)
  Ishpreet Kaur et al.
  4.15
• Financial sentiment analysis using FinBERT with application in predicting stock movement (2023)
  Tingsong Jiang et al.
  4.13
• Multi-period Learning for Financial Time Series Forecasting (2025)
  Xu Zhang and Zhengang Huang and Yunzhi Wu and Xun Lu and Erpeng Qi and Yunkai Chen and Zhongya Xue and Qitong Wang and Peng Wang and Wei Wang
  4.03
• DyWPE: Signal-Aware Dynamic Wavelet Positional Encoding for Time Series Transformers (2025)
  Habib Irani et al.
  3.92
• Time-Transformer: Integrating Local and Global Features for Better Time Series Generation (Extended Version) (2023)
  Yuansan Liu et al.
  3.91
• Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention (2025)
  Sarthak Khanna et al.
  3.86