Showing 1–20 of 25 results
/ Date/ Name
Feb 5, 2025Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language ModelsJun 17, 2025Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMsApr 16, 2019Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event ExtractionNov 6, 2018DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation ExtractionApr 13, 2016A General Distributed Dual Coordinate Optimization Framework for Regularized Loss MinimizationOct 20, 2025Deep Self-Evolving ReasoningOct 23, 2023BatteryML:An Open-source platform for Machine Learning on Battery DegradationOct 11, 2023From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language ModelsJun 18, 2024Large Language Model as a Universal Clinical Multi-task DecoderJan 30, 2024IN-Flow: Instance Normalization Flow for Non-stationary Time Series ForecastingJan 1, 2024DEWP: Deep Expansion Learning for Wind Power ForecastingOct 11, 2023ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction HorizonsNov 4, 2024ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series TransformerMay 26, 2025Are Time-Series Foundation Models Deployment-Ready? A Systematic Study of Adversarial Robustness Across DomainsMar 14, 2026Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral DecompositionMay 2, 2020SEEK: Segmented Embedding of Knowledge GraphsApr 9, 2021Impact of pandemic fatigue on the spread of COVID-19: a mathematical modelling studyJun 14, 2023Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time SeriesOct 8, 2023Accurate battery lifetime prediction across diverse aging conditions with deep learningMar 15, 2022DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting