Cover Image

AION: Next-Generation Tasks and Practical Harness for Time Series

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhan, Tianxiang, Song, Xiaobao, Guan, Tong, Pan, Shirui, Jin, Ming
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TimeOmni-VL: Unified Models for Time Series Understanding and Generation
by: Guan, Tong, et al.
Published: (2026)

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
by: Ge, Yunfeng, et al.
Published: (2025)

TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
by: Guan, Tong, et al.
Published: (2025)

Towards Neural Scaling Laws for Time Series Foundation Models
by: Yao, Qingren, et al.
Published: (2024)

EventTSF: Event-Aware Non-Stationary Time Series Forecasting
by: Ge, Yunfeng, et al.
Published: (2025)

Estimating Time Series Foundation Model Transferability via In-Context Learning
by: Yao, Qingren, et al.
Published: (2025)

End-to-End Learning for Partially-Observed Time Series with PyPOTS
by: Du, Wenjie, et al.
Published: (2026)

Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
by: Hu, Jiaxi, et al.
Published: (2024)

ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models
by: Huang, Bosong, et al.
Published: (2025)

Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases
by: Tan, Zhao, et al.
Published: (2026)

Position: What Can Large Language Models Tell Us about Time Series Analysis
by: Jin, Ming, et al.
Published: (2024)

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
by: Jin, Ming, et al.
Published: (2023)

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
by: Jin, Ming, et al.
Published: (2023)

Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values
by: Zheng, Yu, et al.
Published: (2024)

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
by: Zhang, Kexin, et al.
Published: (2023)

Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
by: Jin, Ming, et al.
Published: (2023)

Deep Learning for Time Series Anomaly Detection: A Survey
by: Darban, Zahra Zamanzadeh, et al.
Published: (2022)

Harnessing Vision Models for Time Series Analysis: A Survey
by: Ni, Jingchao, et al.
Published: (2025)

A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
by: Yang, Yiyuan, et al.
Published: (2024)

D2Vformer: A Flexible Time Series Prediction Model Based on Time Position Embedding
by: Song, Xiaobao, et al.
Published: (2024)

Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
by: Zhan, Tianxiang, et al.
Published: (2024)

Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting
by: Zhan, Tianxiang, et al.
Published: (2025)

Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement
by: Kong, Yaxuan, et al.
Published: (2025)

DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series
by: Darban, Zahra Zamanzadeh, et al.
Published: (2024)

Evaluating Evidential Reliability In Pattern Recognition Based On Intuitionistic Fuzzy Sets
by: Xu, Juntao, et al.
Published: (2024)

Reliability Assessment of Information Sources Based on Random Permutation Set
by: Xu, Juntao, et al.
Published: (2024)

Isopignistic Canonical Decomposition via Belief Evolution Network
by: Zhou, Qianli, et al.
Published: (2024)

Random Graph Set and Evidence Pattern Reasoning Model
by: Zhan, Tianxiang, et al.
Published: (2024)

A Matrix-based Distance of Pythagorean Fuzzy Set and its Application in Medical Diagnosis
by: He, Yuanpeng, et al.
Published: (2021)

Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series
by: Song, Xianhao, et al.
Published: (2026)

Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
by: Kong, Yaxuan, et al.
Published: (2025)

Retrieval-Augmented Generation with Covariate Time Series
by: Liang, Kenny Ye, et al.
Published: (2026)

Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
by: Chen, Katrina, et al.
Published: (2023)

Task-oriented Time Series Imputation Evaluation via Generalized Representers
by: Wang, Zhixian, et al.
Published: (2024)

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation
by: Yang, Silin, et al.
Published: (2024)

TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
by: Wang, Shiyu, et al.
Published: (2024)

Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
by: Liu, Zewen, et al.
Published: (2026)

FilterNet: Harnessing Frequency Filters for Time Series Forecasting
by: Yi, Kun, et al.
Published: (2024)

Learnable WSN Deployment of Evidential Collaborative Sensing Model
by: Liu, Ruijie, et al.
Published: (2024)