Latest
- PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation
- TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis
- Adaptive Collaboration with Humans: Metacognitive Policy Optimization for Multi-Agent LLMs with Continual Learning
- Position: Beyond Prediction: Toward Verifiable Physiological Waveform Reasoning with Foundation Models and Agentic LLMs
- TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Tasks
- "Someone Hid It!": Query-Agnostic Black-Box Attacks on LLM-Based Retrieval
- PINFDiT: Energy-Based Physics-Informed Diffusion Transformers for General-purpose Time Series Tasks
- Conversational Time Series Foundation Models: Towards Explainable and Effective Forecasting
- Topology Matters: Measuring Memory Leakage in Multi-Agent LLMs
- Toward Evolutionary Intelligence: LLM-based Agentic Systems with Multi-Agent Reinforcement Learning
- EnECG: Efficient Ensemble Learning for Electrocardiogram Multi-task Foundation Models
- A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models
- When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference
- Foundation Models for Demand Forecasting via Dual-Strategy Ensembling
- Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting
- When Splitting Makes Stronger: A Theoretical and Empirical Analysis of Divide-and-Conquer Prompting in LLMs
- When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
- Mixture of Projection Experts for Multivariate Long-Term Time Series Forecasting
- Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference
- TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
- An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
- TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
- GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting
- Large Scale Financial Time Series Forecasting with Multi-faceted Model
- SVGformer: Representation Learning for Continuous Vector Graphics using Transformers
- Estimating Treatment Effects in Continuous Time with Hidden Confounders
- Time-delayed Multivariate Time Series Predictions
- DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift
- Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media
- Mu2ReST: Multi-resolution Recursive Spatio-Temporal Transformer for Long-Term Prediction